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Learn more: PMC Disclaimer | PMC Copyright Notice Ann Med . 2026 Apr 12;58(1):2649405. doi: 10.1080/07853890.2026.2649405 Search in PMC Search in PubMed View in NLM Catalog Add to search Development and validation of a self-management efficacy questionnaire for patients with Fabry disease in China Mei-ling Cao Mei-ling Cao a Department of Neonatology, The First Hospital of China Medical University, Shenyang, Liaoning, China Methodology, Resources, Writing – original draft, Writing – review & editing Find articles by Mei-ling Cao a, † , Jia-hui Zou Jia-hui Zou b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China Conceptualization, Data curation, Resources, Software, Writing – original draft, Writing – review & editing Find articles by Jia-hui Zou b, † , Ming-yue Shi Ming-yue Shi b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China Data curation, Formal analysis, Methodology, Validation, Writing – review & editing Find articles by Ming-yue Shi b, † , Yuan-hui Sun Yuan-hui Sun b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China Investigation, Methodology, Resources, Software, Writing – original draft Find articles by Yuan-hui Sun b , Dan-yang Zhao Dan-yang Zhao b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China Data curation, Formal analysis, Resources, Writing – original draft Find articles by Dan-yang Zhao b , Lei Li Lei Li c Department of Orthopaedic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China Formal analysis, Resources, Software, Writing – original draft, Writing – review & editing Find articles by Lei Li c, ✉ , Hong-kun Jiang Hong-kun Jiang b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China Funding acquisition, Resources, Writing – original draft, Writing – review & editing Find articles by Hong-kun Jiang b, ✉ Author information Article notes Copyright and License information a Department of Neonatology, The First Hospital of China Medical University, Shenyang, Liaoning, China b Department of Pediatrics, The First Hospital of China Medical University, Shenyang, Liaoning, China c Department of Orthopaedic Surgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China † These authors contributed equally to this study. Supplemental data for this article can be accessed online at https://doi.org/10.1080/07853890.2026.2649405 . ✉ CONTACT Hong-kun Jiang [email protected] Department of Pediatrics, The First Hospital of China Medical University, No.155 Nanjing North Street, Heping District, Shenyang, 110001, China ✉ Lei Li [email protected] Department of Orthopedic Surgery, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang, 110004, China. Roles Mei-ling Cao : Methodology, Resources, Writing – original draft, Writing – review & editing Jia-hui Zou : Conceptualization, Data curation, Resources, Software, Writing – original draft, Writing – review & editing Ming-yue Shi : Data curation, Formal analysis, Methodology, Validation, Writing – review & editing Yuan-hui Sun : Investigation, Methodology, Resources, Software, Writing – original draft Dan-yang Zhao : Data curation, Formal analysis, Resources, Writing – original draft Lei Li : Formal analysis, Resources, Software, Writing – original draft, Writing – review & editing Hong-kun Jiang : Funding acquisition, Resources, Writing – original draft, Writing – review & editing Received 2025 Sep 23; Accepted 2026 Mar 18; Collection date 2026. © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/ ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. PMC Copyright notice PMCID: PMC13072692 PMID: 41968796 Abstract Background Fabry disease (FD) is a rare X-linked lysosomal storage disorder that impacts the quality of life of patients due to its progressive course, the demands of daily self-management, emotional burden and other subjective experiences. This study aimed to assess the self-management efficacy of patients with FD, identify influencing factors and examine the relationship between quality of life and self-management efficacy to support the development of personalized treatment plans. Methods A cross-sectional study was conducted from March to May 2024 involving 529 patients with FD in China. A clinical assessment tool: the Fabry Disease Self-Management Efficacy Questionnaire (F-SEQ) was developed. Structural validity, internal consistency and test–retest reliability were assessed. Logistic regression analysis was used to identify the factors associated with self-management efficacy. Results The finalized F-SEQ included 42 items and demonstrated good reliability and sensitivity to change. Self-management efficacy scores among patients were moderately low. The total F-SEQ score indicated significant correlations with both the General Self-Efficacy Scale (GSES) and the Study 36-Item Short Form Health Survey. Confidence in medication management was strongly correlated with GSES scores ( p < 0.001). Higher levels of emotional and social management were significantly associated with better social function and reduced physical pain ( p < 0.001). Compared to GSES, the F-SEQ total score showed a stronger correlation with social function and physical pain. Conclusion The F-SEQ is a reliable and valid instrument for assessing self-management efficacy in patients with FD in the Chinese context. It also demonstrated stronger predictive associations with quality-of-life domains than conventional tools, supporting its use in informing personalized intervention strategies aimed at improving patient outcomes. Keywords: Chronic disease, Fabry disease, reliability and validity, self-efficacy, self-management 1. Introduction Fabry disease (FD) is a rare X-linked lysosomal storage disorder resulting from variants in the GLA gene. These variants lead to a deficiency of the enzyme alpha-galactosidase A, causing the accumulation of metabolic substrates, including globotriaosylceramides (GL-3) and their deacylated derivatives, lyso-GL-3, within the kidneys, heart, peripheral nerves, and skin. This progressive substrate accumulation contributes to multisystem organ pathology and may lead to severe, potentially life-threatening complications [ 1 , 2 ]. Incidence rates based on newborn screening range from 1 in 3,859 to 1 in 8,882 across different countries [ 3 , 4 ]. The clinical manifestations of FD are heterogeneous in presentation and severity, with symptoms typically progressing over time. FD is a chronic condition characterized by recurrence and may lead to serious complications such as stroke, renal failure, and cardiovascular disease, resulting in a reduced life expectancy by approximately 15–20 years in males and 6–10 years in females [ 2 , 5 , 6 ]. Due to the non-specific nature of its early symptoms, the diagnostic interval from initial symptom onset to confirmed diagnosis can extend up to 30 years. In China, the diagnostic rate of FD remains low, highlighting a substantial need for improvement in disease recognition and early detection [ 7 ]. The primary therapeutic approach consists of long-term enzyme replacement therapy (ERT), which involves biweekly intravenous administration of agalsidase [ 8 ]. As of current estimates, approximately 1,900 individuals have been diagnosed with FD in China, with around 700 patients receiving ERT. However, a significant proportion of patients still lack access to systematic or individualized treatment plans. Notably, health insurance policy reforms implemented in China in 2021 have contributed to meaningful improvements in access to FD treatment. These estimates are based on data from the Chinese FD Association, as official public records on patient numbers are not available. Along with the challenges associated with diagnosis and treatment, patients with FD frequently experience fatigue, pain, and psychological distress, all of which contribute to a diminished health-related quality of life [ 9 ]. Self-efficacy beliefs play a key role in the regulation of motivation, behaviour and overall well-being [ 10 ]. Psychological interventions have demonstrated effectiveness in alleviating chronic pain symptoms [ 11 ]. Self-management efficacy is particularly important in the context of FD, as it has a significant impact on disease coping and symptom control. Higher levels of general self-efficacy are associated with more active disease management, improved symptom regulation and enhanced quality of life among patients with FD [ 12 ]. However, most existing self-efficacy assessment tools for patients with chronic diseases exhibit notable limitations [ 13 ]. Although Noël et al. developed a self-assessment questionnaire to measure treatment expectations in patients with FD, no specialized instruments are currently available for assessing self-management efficacy in this population [ 14 ]. A detailed comparison of the existing scales is provided in Supplementary Table 1 . In summary, general self-efficacy is of considerable importance for patients with chronic diseases, and the development of an appropriate instrument to assess the self-efficacy of patients with FD is essential [ 15 ]. This study was grounded in self-management theory, integrated the clinical characteristics of FD and adhered to established principles of contemporary scale development [ 15 , 16 , 17 ]. A questionnaire was developed to assess self-management efficacy in patients with FD, and a cross-sectional observational study was conducted based on this instrument. The scale aimed to comprehensively assess self-management efficacy across four dimensions: Emotional Social Management Confidence (ESMC), Treatment Medication Management Confidence (TMMC), Disease Knowledge Management Confidence (DKMC) and Daily Life Management Confidence (DLMC). This study aimed to assess the self-management efficacy of patients with FD, identify the influencing factors, and examine the relationship between quality of life and self-management efficacy to support the development of personalized treatment plans. 2. Methods 2.1. Ethical approval and participation consent Ethical approval for the study was granted by the Ethics Committee of the First Hospital of China Medical University (Approval No.: AF-SOP-07-1.2-01; No. 2024-443). The study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants or their guardians. 2.2. Participants A purposive sampling method was employed, using online recruitment whereby patients with FD were invited to complete the questionnaire. Electronic questionnaires were distributed through the Chinese FD Patients Association and digital platforms, including the FD Forum and a WeChat official account, for participant recruitment. Access to the questionnaire was provided via a secure network link, and anonymous informed consent was obtained online prior to participation. Participants were included if a confirmed diagnosis of FD had been established and the questionnaire was completed voluntarily and accurately. For participants under the age of 10, guardians were instructed to explain the questions and assist only with the general data section; responses were not permitted to be completed on behalf of the child. The initial version of the questionnaire consisted of 54 items. A total of 531 questionnaires were received, of which 529 were deemed valid, resulting in an effective response rate of 99.6%. 2.3. Study design 2.3.1. Item generation The study was conducted at The First Hospital of China Medical University between March and May 2024. Patients diagnosed with FD across China were recruited to participate in an online questionnaire survey. Questionnaire content was developed through a literature review using databases such as PubMed and Web of Science, with search terms including ‘Fabry disease (FD)’, ‘treatment’, ‘complications’ and ‘prognosis’. In addition, items from existing chronic disease self-management and quality of life scales related to social function (SF) were incorporated to supplement item development. Following initial item generation, the preliminary version of the questionnaire, consisting of 54 items, was completed by five patients with FD, who were also invited to provide feedback on item clarity and relevance. A 100% completion rate was observed, with an average completion time of 240.5 s. Based on participant feedback, no modifications were made to the questionnaire items. Study data and secure access links were provided after online-informed consent was obtained. The survey was completed anonymously via an online platform. As a result, a 54-item prototype questionnaire to assess the self-management efficacy in FD was established. 2.3.2. Item evaluation Critical ratio method: Total questionnaire scores were calculated and ranked in ascending order. The lowest 27% of scores were classified into the low-score group, and the highest 27% were classified into the high-score group. An independent samples t -test was conducted to compare item scores between the two groups. Items with a critical ratio value of less than 3 were excluded from subsequent analysis. Item–total correlation analysis (I-T analysis): Correlation coefficients were calculated between the score of each item and the total questionnaire score. Items with a correlation coefficient below 0.4 were removed from further analysis. 2.4. Psychometric evaluation 2.4.1. Content validity Seven experts representing the fields of nephrology, cardiology, dermatology, neurology, paediatrics, neuropsychology, and rehabilitation were invited to assess the content validity of the questionnaire. The Content Validity Index (CVI) was used, comprising the Item-level Content Validity Index (I-CVI) and the Scale-level CVI/Average (S-CVI/Ave). The I-CVI was calculated as the proportion of experts assigning a score of 3 or 4 to each item, divided by the total number of experts. The S-CVI/Ave was obtained by summing all I-CVI values and dividing by the total number of items. An I-CVI ≥ 0.78 and an S-CVI/Ave ≥ 0.90 were considered indicative of acceptable content validity. 2.4.2. Construct validity Structural validity was assessed using factor analysis, which included both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). 2.4.3. Cross-sectional validation measures Participants were asked to complete two instruments: the social function, physical pain and physical function dimensions of the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36), and the General Self-Efficacy Scale (GSES) to assess convergent and divergent validity. 2.4.4. Reliability analysis The reliability of the FD Self-Management Efficacy Questionnaire (F-SEQ) was assessed through internal consistency and test–retest reliability. Cronbach’s α coefficient was used to assess the internal consistency of the overall questionnaire as well as its individual items. Test–retest reliability, which reflects the temporal stability of the instrument, was assessed by requesting participants to complete the F-SEQ a second time, two weeks later. The Pearson’s correlation coefficient between the two sets of scores was calculated to assess test–retest reliability. 2.5. Statistical analysis Statistical analyses were conducted using SPSS, version 27 (IBM SPSS Statistics, Armonk, NY). EFA was carried out using principal component analysis with orthogonal rotation to maximize variance and eliminate redundant items, thereby refining the questionnaire. CFA was conducted to validate the structural integrity of the scale. Internal consistency was assessed using Cronbach’s α coefficient, while Pearson’s bivariate correlation coefficients were calculated to assess consistency across the scale’s dimensions. Test–retest reliability was assessed using the intraclass correlation coefficient. Hierarchical regression analysis was conducted to examine whether the F-SEQ significantly predicted quality of life scores while controlling for general self-efficacy (GSE). All statistical tests were two-tailed, with a significance level set at p < 0.05. 3. Results 3.1. Participant characteristics A total of 531 participants were initially recruited, of which 529 completed valid questionnaires, yielding an effective response rate of 99.6%. Among the participants, 57.8% were male, 49.8% had attained a college or university degree or higher, 41.4% were married and 30.8% were employed. Participant ages ranged from 5 to 75 years, with a mean age of 30.41 ± 10.92 years and a median age of 27 years. Detailed demographic and clinical characteristics are presented in Table 1 . The geographical distribution of participants across China is presented in Figure 1 . Table 1. Sociodemographic and clinical characteristics of the participants ( n = 529). Subjects Frequency N (%) Age (years) ≤18 24 4.5 >18 505 95.5 Gender Male 306 57.8 Female 223 42.2 Educational level Secondary school or below 133 25.1 Middle vocational /high school 133 25.1 High vocational /college 186 35.2 Master or above 77 14.6 Employment situation Working 163 30.8 Retired 80 15.1 Unemployed 110 20.8 Farming 73 13.8 Others 103 19.5 Marital status Unmarried 156 29.5 Married 219 41.4 Divorced 79 14.9 Others 75 14.2 Family Monthly Income (per capita, CNY) <3,000 190 35.9 3,000–5,000 148 28 5,000–10,000 107 20.2 >10,000 84 15.9 Annual treatment cost/ annual household income <25% 127 24 25 ∼ 50% 134 25.3 50%∼75% 140 26.5 >75% 128 24.2 Fabry disease clinical manifestations* Classic form 295 55.8 Late-onset form 234 44.2 Age of onset (years) <18 225 42.5 18 ∼ 45 177 33.5 >45 127 24 Disease course(years) <1 106 20 1 ∼ 10 204 38.6 >10 219 41.4 Family history Yes 338 63.9 No 191 36.1 Cardiac / renal / brain involvement Yes 322 60.9 No 207 39.1 Treatment Enzyme Replacement Treatment (ERT) 263 49.7 Molecular-chaperone / enzyme-enhancing therapy (migalastat) 53 10 Stem-cell and gene-targeted therapy* 67 12.7 Symptomatic treatment* 58 11 No intervention 88 16.6 Current disease treatment status Good 178 33.6 Commonly 218 41.2 Bad 133 25.1 Combined with other diseases Yes 266 50.3 No 263 49.7 Open in a new tab Note: *Fabry disease clinical manifestations[ 18 ] The classic form usually presents in childhood, with enzyme activity absent or significantly decreased. Clinical manifestations include peripheral nervous system symptoms, corneal vortex opacities, angiokeratomas and gastrointestinal discomfort in childhood, and involvement of the heart, kidneys and central nervous system in adulthood. The late-onset form mainly presents after adulthood, with normal enzyme activity in some patients, and the main clinical manifestations are heart and kidney involvement. *The stem-cell and gene-targeted therapy data is derived from the patients’ self-reports. Currently, there are no publicly available peer-reviewed and formally published or standardized treatment process documents in China. Therefore, this study only presents the statistics and does not provide specific technical details and efficacy analysis. *Symptomatic treatment refers to therapeutic approaches aimed solely at relieving or controlling clinical manifestations and discomfort. Figure 1. Open in a new tab Geographical distribution map of patients with FD in China. Note: The figure includes data only from participants whose IP addresses were located within China. 3.2. Item evaluation The initial version of the FD self-management scale, developed through an extensive literature review and interview-based analysis, consisted of 54 items. Based on item analysis, Item 30: the fourth dietary-management item was retained, as it demonstrated a p value of 0.113 and a corrected item-total correlation coefficient of ≥ 0.4. Detailed results are presented in Supplementary Material Table 2 . 3.3. Psychometric evaluation 3.3.1. Content validity The questionnaire was assessed by seven experts, resulting in a S-CVI/Ave of 0.923, with I-CVI values ranging from 0.79 to 1.00. The final version of the questionnaire consists of 42 items, organized into four dimensions: Emotional and Social Management Confidence (13 items), TMMC (12 items), DKMC (10 items) and DLMC (7 items). 3.3.2. Construct validity EFA was conducted to assess the structural validity of the FD self-management efficacy questionnaire. The Kaiser-Meyer-Olkin measure for the 54-item questionnaire was 0.986, indicating excellent sampling adequacy. Bartlett’s Test of Sphericity yielded a value of 31,122.841 ( p < 0.001), confirming the suitability of the data for factor analysis. Principal component analysis with orthogonal rotation was performed to maximize variance. Following four iterative rounds of exploration, 12 items were removed from the original 54-item version, resulting in a refined 42-item questionnaire. These items were grouped into four factors, named according to item content and clinical relevance: ESMC (13 items), TMMC (12 items), DKMC (10 items), and DLMC (7 items). Detailed results are presented in Table 2 . Table 2. Item factor loadings ( n = 529). Item Factor1 Factor2 Factor3 Factor4 45.When I can’t relieve my bad emotions, I can take the initiative to tell others 0.818 0.269 0.222 0.202 53.I can honestly express my disease to my teachers and friends 0.815 0.284 0.150 0.176 46.I can take the initiative to express my thoughts and feelings with my family during the treatment 0.794 0.288 0.206 0.243 52.When I feel pain, I can ask my teachers or classmates for help 0.790 0.254 0.138 0.229 48. When I am in trouble, I can ask my family or friends for comfort and help 0.781 0.258 0.238 0.237 44. When I am depressed, I can mediate with myself 0.761 0.288 0.307 0.189 47. I can maintain close relationships, show concern for my family and friends, and participate in social activities 0.726 0.284 0.320 0.260 54. I can concentrate in my study or in my life 0.705 0.389 0.196 0.237 49.I can take the initiative to know the patients, and actively participate in the social activities of the patients 0.699 0.346 0.237 0.326 35.I can keep a detailed record of the daily symptoms (fever, pain, diarrhea, abdominal pain and other gastrointestinal symptoms) 0.670 0.270 0.079 0.408 43.During the illness, I can keep a positive attitude 0.659 0.383 0.343 0.207 50.I can consult the medical staff about the disease related knowledge and questions during the diagnosis and treatment process 0.609 0.385 0.328 0.305 51.During the treatment, I can communicate well with the medical staff 0.563 0.356 0.362 0.315 7.I have the ability to take my medication on time 0.457 0.687 0.148 0.238 6.I know when to have the medication 0.286 0.674 0.373 0.192 9.I believe that regular medication can control the condition 0.290 0.670 0.343 0.278 8.I fully trust my doctor / hospital 0.255 0.664 0.341 0.265 10 I know that regular clinical monitoring is required 0.275 0.664 0.388 0.269 4. I know the precautions of using agarsylase 0.364 0.664 0.294 0.261 12. I can afford to go to the hospital for monitoring on time 0.478 0.660 0.232 0.187 11. I know the time to go to the hospital to monitor the organ function 0.378 0.658 0.267 0.307 5. I know the importance of a premedication assessment 0.377 0.652 0.317 0.266 2. I know what agatoridase does 0.301 0.649 0.413 0.134 1. I know the main treatment method for Fabry’s disease 0.351 0.637 0.346 0.136 14. I know when I might go to the hospital because of the disease progression 0.462 0.624 0.303 0.203 19. I know something about the main clinical manifestations of Fabry’s disease 0.216 0.226 0.814 0.184 20. I know which organs Fabry’s disease can involve 0.207 0.179 0.807 0.250 17.I know that Fabry’s disease is a genetic disease caused by genetic mutations 0.101 0.230 0.804 0.169 16. I know that Fabry disease is a rare disease 0.062 0.198 0.796 0.239 22. I know the possible direction of the disease without treatment 0.262 0.325 0.709 0.213 21. I know which organs I have involved 0.262 0.319 0.693 0.186 18. I know about genetic counseling and prenatal diagnosis before childbirth 0.245 0.250 0.687 0.251 24 I know the goal of Fabry’s disease 0.339 0.411 0.632 0.186 25. I can learn the knowledge about Fabry’s disease independently 0.367 0.373 0.607 0.186 23. I know my clinical classification of the disease 0.371 0.364 0.559 0.173 28. I can try to avoid spicy, coffee and other stimulating foods 0.312 0.205 0.234 0.757 29. I can match my diet (low sugar, low salt, low fat, high quality protein) 0.375 0.191 0.287 0.739 30.I can eat regularly, eat less and more meals, and avoid overeating or excessive hunger 0.401 0.262 0.345 0.656 31. I can control my weight properly 0.396 0.271 0.303 0.642 27. I can follow the doctor’s advice and stop smoking and alcohol 0.152 0.279 0.331 0.624 32. I can drink water properly 0.352 0.287 0.371 0.623 34. I can have a regular sleep schedule and get enough sleep 0.456 0.377 0.188 0.561 Open in a new tab To confirm the structural stability and validity of the FD self-management efficacy questionnaire, CFA was conducted on the 42-item version. The results indicated a chi-square to degrees of freedom ratio (χ 2 /df) of 3.946, which falls within an acceptable range. Additional fit indices were as follows: Root Mean Square Error of Approximation = 0.075, Comparative Fit Index = 0.938, Incremental Fit Index = 0.938, Tucker-Lewis Index = 0.935, Parsimonious Normed Fit Index = 0.868 and Parsimony Comparative Fit Index = 0.886, all supporting a good model fit for the four-factor structure. In the analysis of convergent validity, factor loadings ranged from 0.725 to 0.972, all exceeding the threshold of 0.5, with all path coefficients reaching statistical significance ( p < 0.001). Composite reliability values ranged from 0.9628 to 0.9942, all above 0.8, while average variance extracted (AVE) values ranged from 0.6839 to 0.9301, all surpassing the 0.5 criterion. For discriminant validity, the square roots of AVE values ranged from 0.8134 to 0.8527, each greater than the corresponding inter-factor correlation coefficients. Detailed results are presented in Supplementary Figure 1 and Tables 3 and 4 . The final version of the questionnaire is provided in Supplementary Material Table 5 . Table 3. Pearson’s correlations between the F-SEQ scale and the GSES and the SF-36. Item FSEQ total FSEQ subscales ESMC TMMC DKMC DLMC GSEs .625** .596** .600** .555** .508** SF-36 social function (SF) .544** .593** .514** .360** .409** bodily pain (BP) .475** .477** .426** .327** .401** physical functioning (PF) .342** .316** .339** .329** .254** Open in a new tab Note: Data are presented as Pearson’s correlation coefficients to assess how well the F-SEQ agrees with other questionnaires. **: p < 0.05; ***: p < 0.01. Table 4. The cronbach’s α coefficient of FSEQ and all dimensions. All factors and the total questionnaire Number of items Cronbach’s a ESMC 13 0.971 TMMC 12 0.963 DKMC 10 0.950 DLMC 7 0.934 total questionnaire 42 0.983 Open in a new tab Note: Cronbach’s α values exceeding 0.90 indicate excellent internal consistency[ 19 ]. 3.3.3. Cross-sectional validity of the SEQ To assess the relationship between the F-SEQ, the SF-36 and the GSES, Pearson product-moment correlation analyses were conducted. A significant correlation was observed between the total F-SEQ score and overall general self-efficacy ( r = 0.652, p < 0.001), indicating that higher levels of self-management efficacy in FD are associated with stronger general self-efficacy. Significant correlations were also identified between each F-SEQ subscale and the GSES, with TMMC demonstrating the strongest correlation ( r = 0.60, p < 0.001), as presented in Table 3 . In addition, the total F-SEQ score was significantly associated with all dimensions of the SF-36 ( p < 0.01). Higher levels of self-management efficacy in FD were notably associated with improved social functioning and reduced physical pain, with correlations ranging from moderate to low in strength. Emotional and social management confidence demonstrated stronger correlations with both outcomes ( r = 0.59, p < 0.001 for social function; r = 0.48, p < 0.001 for physical pain). Additionally, effective treatment medication management within the self-management efficacy framework was associated with enhanced physical functioning among patients with FD (see Table 3 ). 3.3.4. Internal reliability of the SEQ From internal reliability analysis, the overall Cronbach’s α coefficient for the F-SEQ was calculated at 0.983, indicating excellent internal consistency. Subscale reliability coefficients were found to be high: Emotional and Social Management Confidence at 0.971, TMMC at 0.963, DKMC at 0.950 and DLMC at 0.934, as presented in Table 4 . Split-half reliability was strong, with a coefficient of 0.918 ( p < 0.01). Test–retest reliability, assessed over a 2-week interval, was exceptionally high at 0.992 ( p < 0.01), demonstrating the questionnaire’s temporal stability [ 20 ]. 3.3.5. Incremental validity A moderate positive correlation was identified between the total F-SEQ score and GSE ( r = 0.652, p < 0.001), indicating that the two constructs are related but distinct. Hierarchical regression analysis demonstrated significant incremental predictive validity. When predicting bodily pain scores ( n = 529), GSE, entered first, accounted for 9% of the variance, while the inclusion of F-SEQ contributed an additional 14%. When the order of entry was reversed, F-SEQ accounted for 23% of the variance, whereas GSE explained less than 1%. In predicting SF scores ( n = 529), GSE explained 20% of the variance, and F-SEQ explained 19%. When F-SEQ was entered first, it accounted for 37% of the variance, while GSE contributed only 1%. These findings indicate that the F-SEQ serves as a distinct and robust predictor of social function and physical pain scores, demonstrating greater predictive strength than general self-efficacy (see Table 5 ). Table 5. Hierarchical regression analysis predicting self-care behavior ( N = 529). Item Model 1 Model 2 PF R2 0.133 0.134 Adjusted R2 0.157 0.032 ΔR2 0.031 0.032 ΔF 4.834** 19.821** BP R2 0.09 0.228 Adjusted R2 0.227 0.227 ΔR2 0.143 0 ΔF 24.355** 0.14* SF R2 0.198 0.366 Adjusted R2 0.379 0.379 ΔR2 0.185 0.014 ΔF 39.369** 12.238** Open in a new tab Note: Model 1 means STEP1: GSEs, STEP 2: FSEQ. Model 2 means STEP1: FSEQ, STEP 2: GSES. *: p > 0.05,**: p < 0.05; ***: p < 0.01. 3.4. Correlation study of FD self-management efficacy 3.4.1. Current status of self-management efficacy in patients with FD In this study, the average self-management efficacy score among patients with FD was 104.37 ± 42.97, with 31.4% of individuals scoring above the mean, indicating a moderately low overall level. Among the four assessed dimensions, DKMC recorded the lowest mean score (1.75 ± 0.76), while ESMC showed the highest (2.03 ± 0.95), as detailed in Table 6 . Table 6. Self-management efficacy scores of fabry patients ( n = 529). Item Score Item Average Self-management efficiency 104.37 ± 42.97 2.48 ± 1.02 ESMC 26.47 ± 12.36 2.03 ± 0.95 TMMC 23.09 ± 10.43 1.92 ± 0.87 DKMC 17.51 ± 7.56 1.75 ± 0.76 DLMC 13.36 ± 5.80 1.90 ± 0.83 Open in a new tab 3.4.2. Factors influencing self-management in patients with FD Pearson correlation analysis was conducted to examine the associations between F-SEQ scores and patient characteristics. The results indicated that age and disease duration were positively correlated with all four dimensions and the total score. The annual cost of FD treatment, expressed as a percentage of family income, was positively correlated with Factor 2 and the total score. Higher scores across all four factors and the total score were observed among patients with cardiac, renal, or cerebral involvement, as well as those undergoing ERT. Patients with a family history of FD scored higher in Factors 1, 2, 4, and the total score. In contrast, educational level indicated a negative correlation with Factors 1, 2, 3, and the total score. Per capita monthly family income and age at disease onset were negatively correlated with all four factors and the total score. Female patients scored lower than male patients in Factors 1, 2, 4, and the total score. In addition, patients with the late-onset form of FD scored lower than those with the classic type in Factors 1, 2, 4, and the total score. Detailed results are provided in Table 7 . Table 7. Correlation between the F-SEQ scores and patient characteristics. Item scores Factor1 Factor2 Factor3 Factor4 Total Age (years) 0.419** .364** .287** .308** .391** Gender −0.136** −0.105* −0.076 −0.122** −0.122** Educational level −0.126** −0.170** −0.142** −0.073 −0.148** Family Monthly Income (per capita) −0.248** −0.266** −0.176** −0.183** −0.250** Annual treatment cost/ annual household income 0.08 .127** 0.077 −0.002 .089* Fabry disease type −0.157** −0.144** −0.081 −0.153** −0.149** Age of onset (years) −0.211** −0.150** −0.057 −0.172** −0.167** Disease course(years) .260** .190** .137** .229** .228** Family history −0.164** −0.141** −0.031 −0.123** −0.133** Cardiac/renal/brain involvement −0.284** −0.233** −0.145** −0.230** −0.252** Treatment −0.214** −0.143** −0.119** −0.195** −0.185** Current disease treatment status 0.008 .100* 0.066 0.003 0.052 Combined with other diseases −0.041 −0.071 −0.038 −0.031 −0.053 Open in a new tab Note: * p < 0.05, ** p < 0.01, *** p < 0.001. Factor1: self-efficacy of emotional and social, Factor2: self-efficacy of treatment medication, Factor3: self-efficacy of disease knowledge, Factor4: self-efficacy of daily life management. 4. Discussion To our knowledge, this study constitutes the first investigation into the influence of self-management efficacy on health-related quality of life among patients with FD, using a comparatively large sample size. In patients with Anderson-FD, the accumulation of globotriaosylceramide and related metabolites within the lysosomes of plasma, urine, and various tissues disrupts normal physiological processes and induces irreversible pathological changes. This accumulation contributes to tissue damage and dysfunction in key organs, including the kidneys, heart, and vasculature [ 21 ]. Inadequately managed FD can lead to progressive multisystem involvement, resulting in systemic complications that substantially diminish both quality of life and life expectancy [ 22 ]. Beyond the direct effects of the disease, lifestyle factors such as prolonged physical inactivity have emerged as additional risk contributors to neuropsychological dysfunction in patients with FD [ 23 ]. A treatment approach focused solely on disease-specific interventions is insufficient for slowing disease progression. Subjective factors, including external emotional support and self-management efficacy, are increasingly recognized as key elements in disease trajectory. Prior studies have demonstrated that patients with FD frequently report a lower quality of life in comparison with those with other severe chronic conditions, with negative impacts on psychological health and social engagement [ 24 ]. These findings underscore the necessity of addressing subjective and psychosocial components as part of a comprehensive disease management strategy. Therefore, the influence of self-management efficacy on quality of life in patients with FD was examined and analysed. The findings of this study indicate that the current level of self-management among patients with FD is moderately low. Among the four assessed dimensions, DKMC received the lowest scores, whereas ESMC received the highest. To maintain the scientific rigor of the analysis, insights from previous research on questionnaire validation were reviewed and incorporated [ 25–28 ]. Multiple methods were used to assess the validity and reliability of the scale. Content validity was supported through expert panel assessments [ 29 ]. The four-factor model derived from EFA effectively accounted for the overall variance, and CFA further validated the structural coherence of the four-factor model [ 30 ]. In terms of concurrent validity, correlations were established between the F-SEQ subscales and both the GSES and the SF-36. The questionnaire demonstrated strong internal consistency and construct validity. In summary, these results provide preliminary structural validation of the 42-item self-management scale specifically developed for patients with FD and support the F-SEQ as a reliable instrument for predicting quality of life in this population. Significant correlations were observed between self-management levels in patients with FD and various factors, including age, involvement of additional organs, family income and annual treatment expenditure, disease duration, age at onset, clinical phenotype, educational attainment, family history, sex, and ERT, consistent with findings reported in previous studies. In a study by Arends et al. involving 286 adult patients with FD, quality of life was associated with sex, phenotype, age, and disease duration, with longer disease duration correlating with reduced quality of life, a conclusion further supported by recent investigations [ 31 , 32 ]. Furthermore, in this study, patients with longer disease duration and those with a family history of FD exhibited higher levels of general self-efficacy, which may reflect greater familiarity and experience in managing the condition over time. In contrast to some prior findings, lower self-management efficacy particularly in the emotional and social management dimension was observed among female patients, diverging from earlier reports [ 33 ]. Previous research has indicated that male patients with the classic FD phenotype are at increased risk of adverse events, including cardiovascular outcomes, potentially influenced by lifestyle-related factors such as alcohol use and smoking behaviours [ 34 , 35 ]. Additionally, the association between sex and quality of life varies with age; younger male patients have been reported to experience lower quality of life compared to their female counterparts, with this disparity increasing with age, particularly among women [ 36 ]. Patients with FD require continuous and vigilant lifelong monitoring to mitigate the progressive impact of the disease on multiple organ systems. As the condition advances, chronic cardiac, renal, and neurological complications frequently emerge, potentially reducing life expectancy and necessitating extensive supportive care [ 37–39 ]. The importance of close and proactive monitoring has been emphasized in previous studies as essential for understanding the natural course of the disease and for managing its progression effectively [ 40–42 ]. In recent decades, increasing attention has been directed toward self-management in patients with FD, with recognition that internal emotional factors, along with physical symptoms, play a significant role in daily functioning. In 2012, Ramaswami et al. proposed the development of a valid and reliable tool to monitor treatment progress, resulting in the creation of the 24-item Fabry Patient Health Progress Questionnaire (FPHPQ). This instrument assesses the severity of common FD-related symptoms and has demonstrated correlations with physical health and social domains assessed by the Kindl questionnaire [ 43 ]. Several other tools have been employed to assess quality of life in individuals with FD, including the SF-36, the EuroQol Five-Dimension questionnaire, and the Brief Pain Inventory, all of which are referenced in this study [ 44 , 45 ]. Psychological difficulties are commonly observed among patients with FD. Prior studies have reported that the prevalence of depression in this population ranges from 15% to 62% [ 46 ]. In a more recent study, Körver et al. (2020) examined the relationship between FD and depressive symptoms, noting improvements in depression scale scores following active disease management or the provision of external emotional support. Routine assessment of depressive symptoms was recommended as part of the follow-up care for patients with FD [ 47 ]. When compared to the previously established FPHPQ, the current scale demonstrated strong validity and reliability. Furthermore, it incorporates assessment of emotional management, extending beyond the scope of traditional quality-of-life assessments used in patients with FD. The findings highlight that effective emotional and social management remains a significant challenge, with a notable impact on patients’ perception of physical pain, consistent with conclusions from prior research. In future studies, mental health history will be included as part of the basic demographic and clinical data. The impact of the F-SEQ on mental health disorders will be assessed, and relevant analyses will be conducted to account for psychosocial confounding factors. Furthermore, the 42-item F-SEQ was validated as a reliable and effective self-report instrument for assessing social function and physical pain in patients with FD, demonstrating superior predictive capacity compared to the GSES. Improved understanding of the theoretical aspects of FD treatment particularly relating to medication management was associated with enhanced physical functioning in patients with FD. From the associations with health outcomes identified in this study, strengthening patients’ capacity to manage treatment regimens, while ensuring access to emotional support and psychological counselling, should be prioritized by healthcare professionals and family caregivers. Given the variability in clinical presentation and disease progression, particularly among patients with non-classical phenotypes, the F-SEQ may serve as a valuable tool for clinicians to assess current self-management status and tailor treatment strategies accordingly [ 48 ]. Several limitations of this study should be acknowledged. First, the cross-sectional design limits the ability to establish causal relationships between self-management efficacy and quality of life outcomes. Second, the study sample was limited to Chinese participants, which may restrict the generalizability of the findings to populations of different racial or regional backgrounds. In addition, self-management behaviours were assessed through self-reported data, which may introduce response bias and lack objective verification. The study cohort included 10 minor children. Given the small sample size and the allowance in the questionnaire for guardians to assist minors in understanding the items, the psychometric properties of the scale have not yet been independently validated for this subgroup. As the current study represents the initial development and preliminary validation phase of the F-SEQ, multi-group validation analyses have not yet been performed. However, the observed sex-related heterogeneity in patients with FD warrants further investigation. Future research should include cross-sex measurement invariance testing and differential item functioning analysis to ensure the equivalence of the F-SEQ across male and female patients. Moreover, future cohort studies should incorporate systematic genetic characterization to complement patient-reported outcomes, particularly in the context of mutation-specific treatment response evaluation. Including observational data from healthcare professionals may help verify the actual frequency and quality of self-care activities performed by patients with FD. Longitudinal studies are planned to further examine potential causal relationships among self-efficacy, physical pain, and emotional factors, with the goal of refining intervention strategies aimed at improving both quality of life and the long-term prognosis of patients with FD. 5. Conclusion In conclusion, the 42-item F-SEQ developed in this study was a reliable and effective self-report instrument for assessing self-management confidence in patients with FD. The scale serves as a practical tool for informing self-management interventions within clinical practice. Regular completion of the F-SEQ either prior to clinical appointments or as part of routine monitoring is recommended, as this can help identify areas where additional support may be required. Such insights may assist in enhancing the capacity of patients to manage their condition more effectively. The results derived from the F-SEQ can enable healthcare providers to identify patients with lower self-management capabilities and highlight specific domains in need of improvement, thereby supporting the implementation of targeted intervention strategies and health education programs. Supplementary Material Supplementary materials.docx IANN_A_2649405_SM8588.docx (260.7KB, docx) Acknowledgements We sincerely thank the Fabry Community of China for their invaluable support in distributing the questionnaire and facilitating patient recruitment for this study. We also express our gratitude to all patients who participated in the survey. Glossary Abbreviations Ave Average AVE Average Variation Extraction value BP Bodily pain CFA Confirmatory factor analysis CFI Comparative fit index CR Composite Reliability CVI Content Validity Index DKMC Disease knowledge management confidence DLMC Daily life management confidence EFA Exploratory factor analysis ERT Enzyme Replacement Therapy ESMC Emotional social management confidence FD Fabry disease F-SEQ Fabry Disease Self-Management Efficacy Questionnaire GL-3 Globotriaosylceramides GSE General Self-Efficacy GSES General Self-Efficacy Scale ICC Intra-class correlations ICVI Item-level CVI IFI Incremental fit index IPCFI Parsimonious comparative-of-fit index PF Physical functioning PNF Parsimonious normed-of-fit RMSEA Root mean square error of approximation SCVI Scale-level CVI SF Social function SF-36 Medical Outcomes Study 36- Item Short Form Health Survey TLI Tucker-Lewis Index TMMC Treatment medication management confidence X2/df Chi-squared degree of freedom Funding Statement This study was funded by the following: National Natural Science Foundation of China (No.81300130); Science and Technology Projects for People’s Livelihood of Liaoning Province (2021JH/10300008); Basic Research Projects of Liaoning Province (JYTMS20230073); Provincial Natural Science Foundation Joint Fund of Liaoning (2023-BSBA-363). Ethics approval and consent to participate This study was conducted with approval from the Ethics Committee of the First Hospital of China Medical University (Approval No.: AF-SOP-07-1.2-01; No. 2024-443). This study was conducted in accordance with the declaration of Helsinki. Written informed consent was obtained from all participants or patient guardians. Consent for publication Not applicable. Clinical trial number Not applicable. Disclosure statement The authors declare that they have no competing interests. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. References 1. Zarate YA, Hopkin RJ.. Fabry’s disease. Lancet. 2008;372(9647):1427–1435. doi: 10.1016/S0140-6736(08)61589-5. [ DOI ] [ PubMed ] [ Google Scholar ] 2. Germain DP, Altarescu G, Barriales-Villa R, et al. 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Supplementary Materials Supplementary materials.docx IANN_A_2649405_SM8588.docx (260.7KB, docx) Data Availability Statement The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. 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