Lin-Feng Zhou, Tao Jiang, Xiao-Qin Zhang, Zhi-Rong Li
{"title":"影响腰椎间盘突出症患者术后运动恐惧症发生的因素。","authors":"Lin-Feng Zhou, Tao Jiang, Xiao-Qin Zhang, Zhi-Rong Li","doi":"10.1097/MD.0000000000043096","DOIUrl":null,"url":null,"abstract":"<p><p>This study was intended to analyze the potential risk factors associated with postoperative onset of kinesiophobia in patients with lumbar disc herniation and to construct a predictive model using logistic regression and decision tree methods. We retrospectively evaluated the clinical data of 342 lumbar disc herniation patients who underwent surgical treatment between January 2021 and December 2023, grouped them according to the occurrence of postoperative kinesiophobia, applied multifactorial logistic regression to determine the main influencing factors, and constructed a prediction model with the help of SPSS Modeler software to further evaluate its predictive effect. The study found that the incidence of kinesiophobia was 37.46%; statistically significant differences were found between the kinesiophobia group and the nonkinesiophobia group in terms of education level, visual analog scale (VAS) score of pain, Hospital Anxiety and Depression Scale (HADS) score, self-efficacy, per capita monthly family income, and mode of payment of medical expenses (P < .05). Multifactorial Logistic regression suggested that all of the above factors were independent influencing variables of kinesiophobia (P < .05). Decision tree modeling revealed that self-efficacy was the first discriminant variable, followed by payment method, VAS, HADS score, and income level. Analysis of the subjects' job characteristic curve (receiver operating characteristic) showed that the predictive power of the decision tree model was significantly better than that of the logistic regression model (P < .05). Education level, VAS score, HADS score, self-efficacy, family financial status, and payment mode are all important risk factors for postoperative kinesiophobia, and the use of predictive modeling can be more effective in assessing the patient's condition and realizing early intervention.</p>","PeriodicalId":18549,"journal":{"name":"Medicine","volume":"104 26","pages":"e43096"},"PeriodicalIF":1.3000,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212780/pdf/","citationCount":"0","resultStr":"{\"title\":\"Factors influencing the occurrence of postoperative kinesiophobia in patients with lumbar disc herniation.\",\"authors\":\"Lin-Feng Zhou, Tao Jiang, Xiao-Qin Zhang, Zhi-Rong Li\",\"doi\":\"10.1097/MD.0000000000043096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study was intended to analyze the potential risk factors associated with postoperative onset of kinesiophobia in patients with lumbar disc herniation and to construct a predictive model using logistic regression and decision tree methods. We retrospectively evaluated the clinical data of 342 lumbar disc herniation patients who underwent surgical treatment between January 2021 and December 2023, grouped them according to the occurrence of postoperative kinesiophobia, applied multifactorial logistic regression to determine the main influencing factors, and constructed a prediction model with the help of SPSS Modeler software to further evaluate its predictive effect. The study found that the incidence of kinesiophobia was 37.46%; statistically significant differences were found between the kinesiophobia group and the nonkinesiophobia group in terms of education level, visual analog scale (VAS) score of pain, Hospital Anxiety and Depression Scale (HADS) score, self-efficacy, per capita monthly family income, and mode of payment of medical expenses (P < .05). Multifactorial Logistic regression suggested that all of the above factors were independent influencing variables of kinesiophobia (P < .05). Decision tree modeling revealed that self-efficacy was the first discriminant variable, followed by payment method, VAS, HADS score, and income level. Analysis of the subjects' job characteristic curve (receiver operating characteristic) showed that the predictive power of the decision tree model was significantly better than that of the logistic regression model (P < .05). Education level, VAS score, HADS score, self-efficacy, family financial status, and payment mode are all important risk factors for postoperative kinesiophobia, and the use of predictive modeling can be more effective in assessing the patient's condition and realizing early intervention.</p>\",\"PeriodicalId\":18549,\"journal\":{\"name\":\"Medicine\",\"volume\":\"104 26\",\"pages\":\"e43096\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212780/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/MD.0000000000043096\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/MD.0000000000043096","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Factors influencing the occurrence of postoperative kinesiophobia in patients with lumbar disc herniation.
This study was intended to analyze the potential risk factors associated with postoperative onset of kinesiophobia in patients with lumbar disc herniation and to construct a predictive model using logistic regression and decision tree methods. We retrospectively evaluated the clinical data of 342 lumbar disc herniation patients who underwent surgical treatment between January 2021 and December 2023, grouped them according to the occurrence of postoperative kinesiophobia, applied multifactorial logistic regression to determine the main influencing factors, and constructed a prediction model with the help of SPSS Modeler software to further evaluate its predictive effect. The study found that the incidence of kinesiophobia was 37.46%; statistically significant differences were found between the kinesiophobia group and the nonkinesiophobia group in terms of education level, visual analog scale (VAS) score of pain, Hospital Anxiety and Depression Scale (HADS) score, self-efficacy, per capita monthly family income, and mode of payment of medical expenses (P < .05). Multifactorial Logistic regression suggested that all of the above factors were independent influencing variables of kinesiophobia (P < .05). Decision tree modeling revealed that self-efficacy was the first discriminant variable, followed by payment method, VAS, HADS score, and income level. Analysis of the subjects' job characteristic curve (receiver operating characteristic) showed that the predictive power of the decision tree model was significantly better than that of the logistic regression model (P < .05). Education level, VAS score, HADS score, self-efficacy, family financial status, and payment mode are all important risk factors for postoperative kinesiophobia, and the use of predictive modeling can be more effective in assessing the patient's condition and realizing early intervention.
期刊介绍:
Medicine is now a fully open access journal, providing authors with a distinctive new service offering continuous publication of original research across a broad spectrum of medical scientific disciplines and sub-specialties.
As an open access title, Medicine will continue to provide authors with an established, trusted platform for the publication of their work. To ensure the ongoing quality of Medicine’s content, the peer-review process will only accept content that is scientifically, technically and ethically sound, and in compliance with standard reporting guidelines.