Rasch Analysis of the 25-Question Geriatric Locomotive Function Scale in Japanese Older Adults with Musculoskeletal Disorders: Identifying Age-Related Differences in Item Difficulty and Misfitting Items

Rasch Analysis of the 25-Question Geriatric Locomotive Function Scale in Japanese Older Adults with Musculoskeletal Disorders: Identifying Age-Related Differences in Item Difficulty and Misfitting Items | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Rasch Analysis of the 25-Question Geriatric Locomotive Function Scale in Japanese Older Adults with Musculoskeletal Disorders: Identifying Age-Related Differences in Item Difficulty and Misfitting Items Masaki Nakano, Tatsunori Ikemoto, Young-Chang Arai, Nobunori Takahashi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6002959/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Locomotive syndrome (LS), a condition characterized by diminished mobility due to musculoskeletal disorders, is a growing concern among older adults. The 25-item Geriatric Locomotive Function Scale (GLFS-25) is a common tool for LS assessment. However, its reliance on classical test theory and the inclusion of non-motor function items raise questions about its accuracy in reflecting motor dysfunction severity. This study aimed to evaluate the GLFS-25's psychometric properties using Rasch analysis, focusing on item difficulty variations between young-old (60–74 years) and old-old (75–89 years) individuals with musculoskeletal disorders (MSDs). Methods This cross-sectional study recruited 1000 outpatients (500 young-old and 500 old-old) with MSDs. Participants completed the GLFS-25. Rasch analysis was performed using Winsteps software to assess item difficulty, person ability, and item fit. Wright person-item maps were generated to visualize the distribution of item difficulty and person ability. Infit and outfit mean-square values were used to identify misfitting items. Results The mean age of participants was 73.8 ± 6.8 years. Mean GLFS-25 scores were 26.4 ± 22.3 (young-old) and 35.1 ± 23.0 (old-old). Cronbach's alpha exceeded 0.95 in both groups. Significant differences in LS severity proportions were observed between age groups (p < 0.001). Wright maps revealed a scarcity of items discriminating among low-scoring individuals, particularly in the young-old group. Items related to dressing, toilet use, and bathing were most discriminating for high-scoring individuals. Neck/upper limb pain and social engagement were identified as misfitting items across both age groups. Back/lower back/buttock pain and social interaction were misfitting in the young-old and old-old groups, respectively. Conclusions While the GLFS-25 demonstrated excellent internal consistency, Rasch analysis revealed limitations in its ability to discriminate among individuals with low LS scores, particularly in the young-old group. In addition, several misfitting items were identified, suggesting that some items may not contribute effectively to the measurement of LS. Locomotive Syndrome Geriatric Locomotive Function Scale (GLFS-25) Rasch Analysis Musculoskeletal Disorders Figures Figure 1 Figure 2 Figure 3 Background In 2007, the Japanese Orthopaedic Association introduced the concept of locomotive syndrome (LS) to promote musculoskeletal health awareness among older adults. LS is characterized by diminished mobility due to musculoskeletal disorders (MSDs) affecting bones, joints, cartilage, muscles, and nerves.( 1 , 2 ). The 25-item Geriatric Locomotive Function Scale (GLFS-25) is a self-administered LS assessment tool( 3 ). This instrument evaluates pain, paresthesia, motor difficulties, ambulation, and social participation in middle-aged and older individuals. Each item uses a five-point Likert scale (0–4, no impairment to severe impairment), yielding a total score ranging from 0 to 100. Scores of ≥ 7, ≥16, and ≥ 24 denote LS-1, LS-2, and LS-3, respectively ( 4 ). Studies have demonstrated correlations between the GLFS-25 and reduced gait speed ( 5 ), elevated fall risk ( 6 , 7 ), and diminished quality of life in older adults ( 3 , 8 ). Longitudinal studies have further linked the GLFS-25 to LS incidence ( 9 ) and the necessity for long-term care ( 10 , 11 ). With increasing longevity, LS assessment and management have become paramount over the world( 12 – 15 ). However, the GLFS-25 does not directly quantify motor function, encompassing items related to pain, paresthesia, activities of daily living, and anxiety. Consequently, while the instrument assesses LS severity, the total score derived from classical test theory (CTT) may not precisely reflect motor dysfunction severity ( 16 , 17 ). In a prior study, we proposed item reduction to enhance the instrument's efficacy ( 18 ). Nevertheless, GLFS-25 validity and sensitivity have yet to be evaluated using Rasch analysis. Rasch analysis, developed by Georg Rasch ( 19 ), posits that items within a measurement instrument occupy a unidimensional continuum based on difficulty. This model evaluates the congruence between expected and observed scores. Unidimensionality is assessed via goodness-of-fit statistics and principal component analysis (PCA) of residuals. Rasch analysis enhances measurement quality by weighting individual items according to their contribution to the latent trait, enabling raw score transformation into continuous data. Furthermore, it identifies misfitting items that are redundant for precise measurement, facilitating their removal. Rasch analysis is increasingly utilized to refine the design, sensitivity, and validity of healthcare questionnaires.( 20 – 22 ). A recent study indicated that two physical performance measures exhibited greater sensitivity to aging than the GLFS-25, with the GLFS-25 reference value increasing in individuals aged 75 and older ( 23 ). Therefore, this study investigated GLFS-25 characteristics in Japanese older adults using Rasch analysis, focusing on item difficulty variations between young-old (60–74 years) and old-old (75–89 years) individuals with MSDs. Methods Study design This cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines ( 24 ). Sample size Rasch analysis, an item response theory-based method, benefits from larger sample sizes for improved model fit. Specifically, item difficulty and individual ability estimation accuracy is enhanced with sample sizes of 500 or greater ( 25 ). Given the study's objective to detect intergroup item differences, a sample size of 500 per group was determined. Study Participants Participants (young-old: n = 500; old-old: n = 500) were recruited from Aichi Medical University Hospital outpatients between 2018 and 2019. Eligible individuals were invited to complete the GLFS-25 until target sample sizes were achieved for each age stratum. Questionnaires were self-administered with researcher assistance provided as needed. Inclusion criteria were patients aged 60–89 with MSDs. Exclusion criteria were inability to ambulate independently (with or without assistive devices) and confirmed or suspected dementia. The target sample size (n = 1000) was achieved. The Aichi Medical University Hospital Research Ethics Board approved this study (2019-H136), which was conducted in accordance with the Declaration of Helsinki principles. The hospital obtained comprehensive consent for the academic use of treatment-related information (e.g., treatment modalities, progress, and other relevant data) from all patients. Study details were accessible to all eligible participants via the hospital's website. Given the retrospective nature of the study, written informed consent was waived. De-identified data were used exclusively for this study unless individual patients opted out. Outcome Measures GLFS-25 items and response options are presented in Supplemental Table 1. Participants responded to each item (Q1–Q25) on a 5-point scale (0–4, better to worse), yielding total scores from 0 to 100. Higher score indicates worse locomotive syndrome, and scores of ≤ 6, 7–15, 16–23, and ≥ 24 denote no-LS, LS-1, LS-2, and LS-3, respectively ( 4 ) Statistical Analysis Rasch analysis, a probabilistic logistic model generating logit values for item difficulty and person ability, was performed using Winsteps version 5.2.2 software ( https://www.winsteps.com/ ). This analysis transforms raw scores into continuous data by weighting each item's contribution to the latent trait. Wright person-item maps were generated for all participants and age subgroups to visualize item difficulty and person ability distributions, illustrating items suitable for discriminating between low- and high-scoring individuals. Maps were also constructed for each LS severity group. The Rasch model assumes item unidimensionality and quantifies each item's contribution to the assumed construct. Logit values are probabilistically interpretable. Higher logit values indicate a greater probability of higher scores for individuals with higher overall scores. Infit and outfit mean-square values, derived from residuals, were examined. Items perfectly aligned with the unidimensional scale have an expected statistic of 1. Infit values are weighted statistics, while outfit values are unweighted and more sensitive to outliers. Items with infit/outfit values ≤ 1.5 were deemed acceptable ( 26 ). Therefore, items exceeding this threshold for both infit and outfit were considered misfitting. Cronbach's alpha and chi-squared tests for LS severity proportions were performed using R version 4.4.2. ( 27 ). Results Participant Characteristics Table 1 presents participant characteristics. The mean age was 73.8 ± 6.8 years. Mean GLFS-25 scores were 26.4 ± 22.3 (young-old) and 35.1 ± 23.0 (old-old). Cronbach's alpha exceeded 0.95 across groups. LS severity proportions differed significantly between age groups (P < 0.001, Table 2 ). Table 1 Characteristics of study participants All participants (60–89 years: n = 1000) Young-Old (60–74 years: n = 500) Old-Old (75–89 years: n = 500) Sex, male/female 385/615 204/296 181/319 Age, years (Mean ± SD, Med) 73.8 ± 6.8, 74.5 68.2 ± 4.0, 68.0 79.4 ± 3.8, 78.0 GLFS-25, points (Mean ± SD, Med) 30.7 ± 23.1, 26.0 26.4 ± 22.3, 20.0 35.1 ± 23.0, 31.0 Cronbach's alpha 0.967 0.968 0.964 SD, standard deviation; Med, median; GLFS-25, 25-question Geriatric Locomotive Function Scale Table 2 Proportions of locomotive syndrome severity No-LS (GLFS-25 ≤ 6) LS-1 (7 ≤ GLFS-25 ≤ 15) LS-2 (16 ≤ GLFS-25 ≤ 23) LS-3 (24 ≤ GLFS-25) All participants, n (%) (male/female) 138 (13.8) (50/88) 191 (19.1) (84/107) 135 (13.5) (55/80) 536 (53.6) (196/340) Young-Old, n (%) (male/female) 96 (19.2) (35/61) 112 (22.4) (49/63) 66 (13.2) (27/39) 226 (45.2) (93/133) Old-Old, n (%) (male/female) 42 (8.4) (15/27) 79 (15.8) (35/44) 69 (13.8) (28/41) 310 (62.0) (103/207) LS, locomotive syndrome; GLFS-25, 25-question Geriatric Locomotive Function Scale P -value for the proportion of locomotive syndrome severity between young-old and old-old subgroups was < 0.001 (chi-squared test). Person and Item Estimates Wright maps (Fig. 1 ) depict item difficulty and person ability distributions by age group. Items such as Q8 (dressing), Q10 (toilet use), and Q11 (bathing) effectively discriminated among high-scoring individuals across groups. Conversely, discriminating items for low-scoring participants, particularly in the young-old group, were scarce. Items such as Q13 (brisk walking), Q21 (sports participation), and Q23 (social engagement), along with pain/paresthesia questions (Q1–Q4), differentiated among mid-range scorers. Stratified by LS severity, while the GLFS-25 effectively discriminated the LS-3 group, appropriate items were deficient within the no-LS, LS-1, and LS-2 groups (Fig. 2 ). Item difficulty logit values are presented in Table 3 . Q8, Q10, and Q11 exhibited high logit values across age groups. Table 3 Item difficulty measures All participants Young-Old Old-Old Measure SE Measure SE Measure SE (logits) (logits) (logits) Q1 -6.00 .37 -9.34 .54 -3.24 .51 Q2 -6.71 .37 -8.55 .54 -5.31 .51 Q3 -7.37 .37 -8.90 .54 -6.26 .51 Q4 -5.75 .37 -7.26 .55 -4.63 .51 Q5 5.35 .43 5.49 .67 5.34 .57 Q6 6.53 .44 7.20 .69 6.17 .58 Q7 7.65 .45 8.13 .71 7.46 .60 Q8 12.29 .51 12.24 .79 12.56 .67 Q9 7.17 .45 7.29 .69 7.21 .59 Q10 12.39 .51 13.19 .81 12.06 .66 Q11 9.34 .47 9.37 .73 9.50 .62 Q12 -3.69 .38 -2.68 .58 -4.61 .51 Q13 -8.70 .37 -7.64 .54 -9.89 .51 Q14 9.63 .48 10.46 .75 9.23 .62 Q15 -5.60 .37 -4.81 .56 -6.41 .51 Q16 4.67 .43 5.62 .67 4.06 .56 Q17 -2.53 .38 -2.34 .58 -2.77 .52 Q18 -1.51 .39 − .33 .60 -2.47 .52 Q19 4.57 .43 4.83 .66 4.47 .56 Q20 -4.76 .37 -4.52 .56 -5.10 .51 Q21 -12.18 .36 -11.70 .53 -13.01 .51 Q22 -1.01 .39 -1.70 .58 − .52 .53 Q23 -10.46 .36 -11.33 .53 -10.00 .51 Q24 1.61 .40 2.91 .63 .66 .53 Q25 -4.93 .37 -5.62 .55 -4.50 .51 SE, standard error Mean-square values (Fig. 3 ) revealed Q1 (neck/upper limb pain) and Q23 (social engagement) as misfitting (infit and outfit ≥ 1.5) across groups. Additionally, Q2 (back/lower back/buttock pain) and Q22 (social interaction) were misfitting in the young-old and old-old groups, respectively. Q7 (indoor ambulation) demonstrated the highest sensitivity across groups. Discussion This study investigated GLFS-25 characteristics and validity in Japanese older adults using Rasch analysis. Cronbach's alpha indicated excellent internal consistency across groups. While the GLFS-25 reflected LS-3 severity, discriminating items for low-scoring individuals, especially in the young-old group, were limited. Furthermore, misfitting items varied between age groups. The JOA developed the GLFS-25 as an LS screening tool ( 3 ). As LS is an epidemiological construct, GLFS-25 assessment, alongside physical function tests, remains an official diagnostic criterion ( 2 ). However, pain and psychological status may be overestimated in younger individuals due to greater social roles and burdens ( 28 ), even with adequate muscle strength and balance. Conversely, reduced social roles and activities in older individuals may result in lower GLFS-25 scores despite motor impairment. Therefore, items and severity levels contributing to locomotive difficulties may vary across age groups. CTT, the most prevalent theory, employs simple mathematical analysis. GLFS-25-based LS assessment also utilizes this theory. However, our findings suggest the validity of utilizing a single composite score for assessing LS severity across all individuals is questionable. Wright person-item maps demonstrated that the items were geared towards middle to high scores on the questionnaire across groups. The median score for all participants was 26.0, suggesting a lack of appropriate questions to differentiate between LS-1 (7–15 points) and LS-2 (16–23 points). Indeed, suitable items were deficient within the no-LS, LS-1, and LS-2 groups, particularly in the young-old subgroup, highlighting the need for improved early LS assessment and management. Misfitting items introduce noise. Analysis revealed Q1 ("neck or upper limbs pain"), Q2 ("back, lower back, or buttocks pain"), Q22 ("meeting friends"), and Q23 ("joining social activities") as misfitting. Of these, Q2 and Q22 were characteristic of the young-old and old-old groups, respectively. These findings suggest that items related to body pain/paresthesia and social activities tend to misfit, with potential intergroup variations. Consistent with our prior study employing confirmatory factor analysis, item refinement may be necessary. Beyond highlighting patient-reported outcome measure (PROM) limitations, our results suggest considering the target population and relevant items when establishing PROM. This study is limited by single-institution recruitment, potentially introducing sampling bias and limiting generalizability. Comorbidities and quality of life were not assessed. Patient background and social environment may be relevant. Elderly patients often have multiple comorbidities influencing LS. Future studies should address concurrent validation. Conclusion This study investigated GLFS-25 characteristics and validity in Japanese older adults using Rasch analysis. Results revealed a lack of suitable items for those with low GLFS-25 scores. Four misfitting items were identified, with intergroup variations. Given the questionnaire's importance alongside physical function tests, GLFS-25 refinement is warranted to improve early LS assessment, management, and awareness. Abbreviations GLFS-25: 25-item Geriatric Locomotive Function Scale LS: Locomotive syndrome MSD: Musculoskeletal disorders CTT: Classical test theory PROM: patient-reported outcome measure Declarations Ethics approval and consent to participate The Aichi Medical University Hospital Research Ethics Board approved this study (2019-H136), which was conducted in accordance with the Declaration of Helsinki principles. The hospital obtained comprehensive consent for the academic use of treatment-related information (e.g., treatment modalities, progress, and other relevant data) from all patients. Study details were accessible to all eligible participants via the hospital's website. Given the retrospective nature of the study, written informed consent was waived. De-identified data were used exclusively for this study unless individual patients opted out. Availability of data and materials The datasets are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy and ethical restrictions. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contributions M.N. and T.I. directed and designed the study. T.I. and Y-C.A. collected the data. M.N. and T.I. analyzed the data and performed the statistical analysis. M.N., T.I., Y-C.A., N.T., and Y.N. interpreted the data. M.N. and T.I. drafted the manuscript. All authors approved the final version of the manuscript for publication. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Acknowledgements We would like to thank all participants in the present study. Competing interests Tatsunori Ikemoto is an editorial member of Health and Quality of Life Outcomes. Masaki Nakano, Young-Chang Arai, Nobunori Takahashi, & Yukio Nakamura have no disclosures regarding the present study. The all authors have no relevant financial or non-financial interests to disclose. References Nakamura K. A “super-aged” society and the “locomotive syndrome.” J Orthop Sci. 2008 Jan;13(1):1–2. Nakamura K, Ogata T. Locomotive Syndrome: Definition and Management. Clin Rev Bone Miner Metab. 2016 May 25;14:56–67. Seichi A, Hoshino Y, Doi T, Akai M, Tobimatsu Y, Iwaya T. 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Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007 Oct 20;335(7624):806–8. Guilleux A, Blanchin M, Hardouin J-B, Sébille V. Power and sample size determination in the Rasch model: evaluation of the robustness of a numerical method to non-normality of the latent trait. PLoS One. 2014 Jan 10;9(1):e83652. Linacre JM. A user’s guide to facets rasch-model computer programs. Available from: https://www.winsteps.com/manuals.htm R Core Team (2023). R: A Language and Environment for Statistical Computing . R Foundation for Statistical Computing, Vienna, Austria. Available from: https://www.R-project.org/ Pourbordbari N, Jensen MB, Olesen JL, Holden S, Rathleff MS. Bio-psycho-social characteristics and impact of musculoskeletal pain in one hundred children and adolescents consulting general practice. BMC Prim Care. 2022 Jan 25;23(1):20. Additional Declarations Competing interest reported. Tatsunori Ikemoto is an editorial member of Health and Quality of Life Outcomes. Masaki Nakano, Young-Chang Arai, Nobunori Takahashi, & Yukio Nakamura have no disclosures regarding the present study. The all authors have no relevant financial or non-financial interests to disclose. Supplementary Files SupTables.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6002959","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":414909429,"identity":"41f608fb-e269-4e60-8fd2-df742b5a94d2","order_by":0,"name":"Masaki Nakano","email":"","orcid":"","institution":"Aichi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Masaki","middleName":"","lastName":"Nakano","suffix":""},{"id":414909430,"identity":"e405d970-223f-4c47-adbd-a73f8fd9eee5","order_by":1,"name":"Tatsunori Ikemoto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDADeWbmA0BKQoagSh4GZgjDsJ0tAaSFh3gtDOd5DCAChIA9+/nDn3l32OQxNvN8fnWjxoKHgf3w0Q14beFJZpPmPZNWzM7Mu8065xjQYTxpaTfwOyyZjZm37XBiYzPvNuMcNqAWCR4z/Fr4HzN/BmlpOMzzzDjnHzFaJJIZpKFamB/nthGj5cZjM8m5bWmJG5vZzJhz+yR42Aj5hb0/8fGHt202ifP5Dz/+nPOtTo6f/fAxvFqQAZsEmCRWOQgwfyBF9SgYBaNgFIwcAAA7xD/74PcUaQAAAABJRU5ErkJggg==","orcid":"","institution":"Aichi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tatsunori","middleName":"","lastName":"Ikemoto","suffix":""},{"id":414909431,"identity":"344cbe55-4281-4515-8750-ae2f2de736c8","order_by":2,"name":"Young-Chang Arai","email":"","orcid":"","institution":"Aichi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Young-Chang","middleName":"","lastName":"Arai","suffix":""},{"id":414909432,"identity":"caf75be3-330e-48f4-835c-66d3b2b79f50","order_by":3,"name":"Nobunori Takahashi","email":"","orcid":"","institution":"Aichi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Nobunori","middleName":"","lastName":"Takahashi","suffix":""},{"id":414909433,"identity":"fd0de345-853d-4df8-b2a2-7ca93446c56e","order_by":4,"name":"Yukio Nakamura","email":"","orcid":"","institution":"Aichi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yukio","middleName":"","lastName":"Nakamura","suffix":""}],"badges":[],"createdAt":"2025-02-11 02:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6002959/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6002959/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76280650,"identity":"006135d1-b7cc-4f84-9f29-476c25acf089","added_by":"auto","created_at":"2025-02-14 10:34:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3462619,"visible":true,"origin":"","legend":"\u003cp\u003eWright person-item map for the GLFS-25 by age group.\u003c/p\u003e\n\u003cp\u003e(A) all participants (60–89 years old)\u003c/p\u003e\n\u003cp\u003e(B) young-old subgroup (60–74 years old)\u003c/p\u003e\n\u003cp\u003e(C) old-old subgroup (75–89 years old)\u003c/p\u003e\n\u003cp\u003eGLFS-25, 25-question Geriatric Locomotive Function Scale\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6002959/v1/4afb370d9b4d47db3f759b46.png"},{"id":76280648,"identity":"1c2b4a4e-2d4e-49d9-ad2c-16cb5d4aabc5","added_by":"auto","created_at":"2025-02-14 10:34:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3369002,"visible":true,"origin":"","legend":"\u003cp\u003eWright person-item map for the GLFS-25 by LS severity.\u003c/p\u003e\n\u003cp\u003e(A) No-LS (≤ 6 points)\u003c/p\u003e\n\u003cp\u003e(B) LS-1 (7–15 points)\u003c/p\u003e\n\u003cp\u003e(C) LS-2 (16–23 points)\u003c/p\u003e\n\u003cp\u003e(D) LS-3 (≥ 24 points)\u003c/p\u003e\n\u003cp\u003eGLFS-25, 25-question Geriatric Locomotive Function Scale; LS, locomotive syndrome\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6002959/v1/a6c7b648e5104619747d319c.png"},{"id":76280649,"identity":"22e2e470-ad5d-4771-b833-6ffbf240fabb","added_by":"auto","created_at":"2025-02-14 10:34:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1017684,"visible":true,"origin":"","legend":"\u003cp\u003eInfit and outfit mean-square values for the GLFS-25 by age group.\u003c/p\u003e\n\u003cp\u003e(A) all participants (60–89 years old)\u003c/p\u003e\n\u003cp\u003e(B) young-old subgroup (60–74 years old)\u003c/p\u003e\n\u003cp\u003e(C) old-old subgroup (75–89 years old)\u003c/p\u003e\n\u003cp\u003eGLFS-25, 25-question Geriatric Locomotive Function Scale; MnSq, mean-square\u003c/p\u003e\n\u003cp\u003eDashed line indicates the mean-square value of 1.5.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6002959/v1/8d917971dd01728943404dbf.png"},{"id":78479897,"identity":"b00dd6e1-63d9-42d3-bbce-0aee3962184c","added_by":"auto","created_at":"2025-03-13 18:31:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8886081,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6002959/v1/af5721ad-e8fc-4081-a7ea-dd0bc76ad969.pdf"},{"id":76280196,"identity":"09e711c3-f4b6-429d-bc44-8fabece8b1ea","added_by":"auto","created_at":"2025-02-14 10:26:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":143689,"visible":true,"origin":"","legend":"","description":"","filename":"SupTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6002959/v1/f31e7d69a985ac98b76751e6.pdf"}],"financialInterests":"Competing interest reported. Tatsunori Ikemoto is an editorial member of Health and Quality of Life Outcomes. Masaki Nakano, Young-Chang Arai, Nobunori Takahashi, \u0026 Yukio Nakamura have no disclosures regarding the present study. The all authors have no relevant financial or non-financial interests to disclose.","formattedTitle":"Rasch Analysis of the 25-Question Geriatric Locomotive Function Scale in Japanese Older Adults with Musculoskeletal Disorders: Identifying Age-Related Differences in Item Difficulty and Misfitting Items","fulltext":[{"header":"Background","content":"\u003cp\u003eIn 2007, the Japanese Orthopaedic Association introduced the concept of locomotive syndrome (LS) to promote musculoskeletal health awareness among older adults. LS is characterized by diminished mobility due to musculoskeletal disorders (MSDs) affecting bones, joints, cartilage, muscles, and nerves.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 25-item Geriatric Locomotive Function Scale (GLFS-25) is a self-administered LS assessment tool(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). This instrument evaluates pain, paresthesia, motor difficulties, ambulation, and social participation in middle-aged and older individuals. Each item uses a five-point Likert scale (0\u0026ndash;4, no impairment to severe impairment), yielding a total score ranging from 0 to 100. Scores of \u0026ge;\u0026thinsp;7, \u0026ge;16, and \u0026ge;\u0026thinsp;24 denote LS-1, LS-2, and LS-3, respectively (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Studies have demonstrated correlations between the GLFS-25 and reduced gait speed (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), elevated fall risk (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and diminished quality of life in older adults (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Longitudinal studies have further linked the GLFS-25 to LS incidence (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) and the necessity for long-term care (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). With increasing longevity, LS assessment and management have become paramount over the world(\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, the GLFS-25 does not directly quantify motor function, encompassing items related to pain, paresthesia, activities of daily living, and anxiety. Consequently, while the instrument assesses LS severity, the total score derived from classical test theory (CTT) may not precisely reflect motor dysfunction severity (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In a prior study, we proposed item reduction to enhance the instrument's efficacy (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Nevertheless, GLFS-25 validity and sensitivity have yet to be evaluated using Rasch analysis.\u003c/p\u003e \u003cp\u003eRasch analysis, developed by Georg Rasch (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), posits that items within a measurement instrument occupy a unidimensional continuum based on difficulty. This model evaluates the congruence between expected and observed scores. Unidimensionality is assessed via goodness-of-fit statistics and principal component analysis (PCA) of residuals. Rasch analysis enhances measurement quality by weighting individual items according to their contribution to the latent trait, enabling raw score transformation into continuous data. Furthermore, it identifies misfitting items that are redundant for precise measurement, facilitating their removal. Rasch analysis is increasingly utilized to refine the design, sensitivity, and validity of healthcare questionnaires.(\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA recent study indicated that two physical performance measures exhibited greater sensitivity to aging than the GLFS-25, with the GLFS-25 reference value increasing in individuals aged 75 and older (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Therefore, this study investigated GLFS-25 characteristics in Japanese older adults using Rasch analysis, focusing on item difficulty variations between young-old (60\u0026ndash;74 years) and old-old (75\u0026ndash;89 years) individuals with MSDs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design\u003c/h2\u003e\n \u003cp\u003eThis cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eRasch analysis, an item response theory-based method, benefits from larger sample sizes for improved model fit. Specifically, item difficulty and individual ability estimation accuracy is enhanced with sample sizes of 500 or greater (\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e). Given the study\u0026apos;s objective to detect intergroup item differences, a sample size of 500 per group was determined.\u003c/p\u003e\n\u003ch3\u003eStudy Participants\u003c/h3\u003e\n\u003cp\u003eParticipants (young-old: n\u0026thinsp;=\u0026thinsp;500; old-old: n\u0026thinsp;=\u0026thinsp;500) were recruited from Aichi Medical University Hospital outpatients between 2018 and 2019. Eligible individuals were invited to complete the GLFS-25 until target sample sizes were achieved for each age stratum. Questionnaires were self-administered with researcher assistance provided as needed. Inclusion criteria were patients aged 60\u0026ndash;89 with MSDs. Exclusion criteria were inability to ambulate independently (with or without assistive devices) and confirmed or suspected dementia. The target sample size (n\u0026thinsp;=\u0026thinsp;1000) was achieved.\u003c/p\u003e\n\u003cp\u003eThe Aichi Medical University Hospital Research Ethics Board approved this study (2019-H136), which was conducted in accordance with the Declaration of Helsinki principles. The hospital obtained comprehensive consent for the academic use of treatment-related information (e.g., treatment modalities, progress, and other relevant data) from all patients. Study details were accessible to all eligible participants via the hospital\u0026apos;s website. Given the retrospective nature of the study, written informed consent was waived. De-identified data were used exclusively for this study unless individual patients opted out.\u003c/p\u003e\n\u003ch3\u003eOutcome Measures\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eGLFS-25 items and response options are presented in Supplemental Table 1. Participants responded to each item (Q1\u0026ndash;Q25) on a 5-point scale (0\u0026ndash;4, better to worse), yielding total scores from 0 to 100. Higher score indicates worse locomotive syndrome, and scores of \u0026le;\u0026thinsp;6, 7\u0026ndash;15, 16\u0026ndash;23, and \u0026ge;\u0026thinsp;24 denote no-LS, LS-1, LS-2, and LS-3, respectively (\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eRasch analysis, a probabilistic logistic model generating logit values for item difficulty and person ability, was performed using Winsteps version 5.2.2 software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.winsteps.com/\u003c/span\u003e\u003c/span\u003e). This analysis transforms raw scores into continuous data by weighting each item\u0026apos;s contribution to the latent trait. Wright person-item maps were generated for all participants and age subgroups to visualize item difficulty and person ability distributions, illustrating items suitable for discriminating between low- and high-scoring individuals. Maps were also constructed for each LS severity group.\u003c/p\u003e\n \u003cp\u003eThe Rasch model assumes item unidimensionality and quantifies each item\u0026apos;s contribution to the assumed construct. Logit values are probabilistically interpretable. Higher logit values indicate a greater probability of higher scores for individuals with higher overall scores. Infit and outfit mean-square values, derived from residuals, were examined. Items perfectly aligned with the unidimensional scale have an expected statistic of 1. Infit values are weighted statistics, while outfit values are unweighted and more sensitive to outliers. Items with infit/outfit values\u0026thinsp;\u0026le;\u0026thinsp;1.5 were deemed acceptable (\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e). Therefore, items exceeding this threshold for both infit and outfit were considered misfitting.\u003c/p\u003e\n \u003cp\u003eCronbach\u0026apos;s alpha and chi-squared tests for LS severity proportions were performed using R version 4.4.2. (\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents participant characteristics. The mean age was 73.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 years. Mean GLFS-25 scores were 26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.3 (young-old) and 35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.0 (old-old). Cronbach\u0026apos;s alpha exceeded 0.95 across groups. LS severity proportions differed significantly between age groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of study participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll participants\u003c/p\u003e\n \u003cp\u003e(60\u0026ndash;89 years: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1000)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYoung-Old\u003c/p\u003e\n \u003cp\u003e(60\u0026ndash;74 years: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOld-Old\u003c/p\u003e\n \u003cp\u003e(75\u0026ndash;89 years: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex, male/female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385/615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e204/296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e181/319\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, Med)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8, 74.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0, 68.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8, 78.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGLFS-25, points\u003c/p\u003e\n \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, Med)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.7\u0026thinsp;\u0026plusmn;\u0026thinsp;23.1, 26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.3, 20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.0, 31.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCronbach\u0026apos;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eSD, standard deviation; Med, median; GLFS-25, 25-question Geriatric Locomotive Function Scale\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eProportions of locomotive syndrome severity\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo-LS\u003c/p\u003e\n \u003cp\u003e(GLFS-25\u0026thinsp;\u0026le;\u0026thinsp;6)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLS-1\u003c/p\u003e\n \u003cp\u003e(7\u0026thinsp;\u0026le;\u0026thinsp;GLFS-25\u0026thinsp;\u0026le;\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLS-2\u003c/p\u003e\n \u003cp\u003e(16\u0026thinsp;\u0026le;\u0026thinsp;GLFS-25\u0026thinsp;\u0026le;\u0026thinsp;23)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLS-3\u003c/p\u003e\n \u003cp\u003e(24\u0026thinsp;\u0026le;\u0026thinsp;GLFS-25)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll participants, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003cp\u003e(male/female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138 (13.8)\u003c/p\u003e\n \u003cp\u003e(50/88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e191 (19.1)\u003c/p\u003e\n \u003cp\u003e(84/107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135 (13.5)\u003c/p\u003e\n \u003cp\u003e(55/80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e536 (53.6)\u003c/p\u003e\n \u003cp\u003e(196/340)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYoung-Old, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003cp\u003e(male/female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (19.2)\u003c/p\u003e\n \u003cp\u003e(35/61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112 (22.4)\u003c/p\u003e\n \u003cp\u003e(49/63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (13.2)\u003c/p\u003e\n \u003cp\u003e(27/39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e226 (45.2)\u003c/p\u003e\n \u003cp\u003e(93/133)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOld-Old, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003cp\u003e(male/female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (8.4)\u003c/p\u003e\n \u003cp\u003e(15/27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (15.8)\u003c/p\u003e\n \u003cp\u003e(35/44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (13.8)\u003c/p\u003e\n \u003cp\u003e(28/41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e310 (62.0)\u003c/p\u003e\n \u003cp\u003e(103/207)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eLS, locomotive syndrome; GLFS-25, 25-question Geriatric Locomotive Function Scale\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value for the proportion of locomotive syndrome severity between young-old and old-old subgroups was \u0026lt;\u0026thinsp;0.001 (chi-squared test).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePerson and Item Estimates\u003c/h3\u003e\n\u003cp\u003eWright maps (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) depict item difficulty and person ability distributions by age group. Items such as Q8 (dressing), Q10 (toilet use), and Q11 (bathing) effectively discriminated among high-scoring individuals across groups. Conversely, discriminating items for low-scoring participants, particularly in the young-old group, were scarce. Items such as Q13 (brisk walking), Q21 (sports participation), and Q23 (social engagement), along with pain/paresthesia questions (Q1\u0026ndash;Q4), differentiated among mid-range scorers. Stratified by LS severity, while the GLFS-25 effectively discriminated the LS-3 group, appropriate items were deficient within the no-LS, LS-1, and LS-2 groups (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eItem difficulty logit values are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Q8, Q10, and Q11 exhibited high logit values across age groups.\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eItem difficulty measures\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAll participants\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eYoung-Old\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eOld-Old\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeasure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeasure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeasure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(logits)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(logits)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(logits)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-7.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-6.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-12.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-11.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-13.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.36\u003c/p\u003e\n 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align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003eSE, standard error\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eMean-square values (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e) revealed Q1 (neck/upper limb pain) and Q23 (social engagement) as misfitting (infit and outfit\u0026thinsp;\u0026ge;\u0026thinsp;1.5) across groups. Additionally, Q2 (back/lower back/buttock pain) and Q22 (social interaction) were misfitting in the young-old and old-old groups, respectively. Q7 (indoor ambulation) demonstrated the highest sensitivity across groups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated GLFS-25 characteristics and validity in Japanese older adults using Rasch analysis. Cronbach's alpha indicated excellent internal consistency across groups. While the GLFS-25 reflected LS-3 severity, discriminating items for low-scoring individuals, especially in the young-old group, were limited. Furthermore, misfitting items varied between age groups.\u003c/p\u003e \u003cp\u003eThe JOA developed the GLFS-25 as an LS screening tool (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). As LS is an epidemiological construct, GLFS-25 assessment, alongside physical function tests, remains an official diagnostic criterion (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, pain and psychological status may be overestimated in younger individuals due to greater social roles and burdens (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), even with adequate muscle strength and balance. Conversely, reduced social roles and activities in older individuals may result in lower GLFS-25 scores despite motor impairment. Therefore, items and severity levels contributing to locomotive difficulties may vary across age groups. CTT, the most prevalent theory, employs simple mathematical analysis. GLFS-25-based LS assessment also utilizes this theory. However, our findings suggest the validity of utilizing a single composite score for assessing LS severity across all individuals is questionable.\u003c/p\u003e \u003cp\u003eWright person-item maps demonstrated that the items were geared towards middle to high scores on the questionnaire across groups. The median score for all participants was 26.0, suggesting a lack of appropriate questions to differentiate between LS-1 (7\u0026ndash;15 points) and LS-2 (16\u0026ndash;23 points). Indeed, suitable items were deficient within the no-LS, LS-1, and LS-2 groups, particularly in the young-old subgroup, highlighting the need for improved early LS assessment and management.\u003c/p\u003e \u003cp\u003eMisfitting items introduce noise. Analysis revealed Q1 (\"neck or upper limbs pain\"), Q2 (\"back, lower back, or buttocks pain\"), Q22 (\"meeting friends\"), and Q23 (\"joining social activities\") as misfitting. Of these, Q2 and Q22 were characteristic of the young-old and old-old groups, respectively. These findings suggest that items related to body pain/paresthesia and social activities tend to misfit, with potential intergroup variations. Consistent with our prior study employing confirmatory factor analysis, item refinement may be necessary.\u003c/p\u003e \u003cp\u003eBeyond highlighting patient-reported outcome measure (PROM) limitations, our results suggest considering the target population and relevant items when establishing PROM.\u003c/p\u003e \u003cp\u003eThis study is limited by single-institution recruitment, potentially introducing sampling bias and limiting generalizability. Comorbidities and quality of life were not assessed. Patient background and social environment may be relevant. Elderly patients often have multiple comorbidities influencing LS. Future studies should address concurrent validation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study investigated GLFS-25 characteristics and validity in Japanese older adults using Rasch analysis. Results revealed a lack of suitable items for those with low GLFS-25 scores. Four misfitting items were identified, with intergroup variations. Given the questionnaire's importance alongside physical function tests, GLFS-25 refinement is warranted to improve early LS assessment, management, and awareness.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGLFS-25: 25-item Geriatric Locomotive Function Scale\u003c/p\u003e\n\u003cp\u003eLS: Locomotive syndrome\u003c/p\u003e\n\u003cp\u003eMSD: Musculoskeletal disorders\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCTT: Classical test theory\u003c/p\u003e\n\u003cp\u003ePROM: patient-reported outcome measure\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Aichi Medical University Hospital Research Ethics Board approved this study (2019-H136), which was conducted in accordance with the Declaration of Helsinki principles. The hospital obtained comprehensive consent for the academic use of treatment-related information (e.g., treatment modalities, progress, and other relevant data) from all patients. \u0026nbsp;Study details were accessible to all eligible participants via the hospital\u0026apos;s website. \u0026nbsp;Given the retrospective nature of the study, written informed consent was waived. De-identified data were used exclusively for this study unless individual patients opted out.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy and ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.N. and T.I. directed and designed the study. T.I. and Y-C.A. collected the data. M.N. and T.I. analyzed the data and performed the statistical analysis. M.N., T.I., Y-C.A., N.T., and Y.N. interpreted the data. M.N. and T.I. drafted the manuscript. All authors approved the final version of the manuscript for publication. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all participants in the present study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTatsunori Ikemoto is an editorial member of Health and Quality of Life Outcomes. Masaki Nakano, Young-Chang Arai, Nobunori Takahashi, \u0026amp; Yukio Nakamura have no disclosures regarding the present study. The all authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNakamura K. A \u0026ldquo;super-aged\u0026rdquo; society and the \u0026ldquo;locomotive syndrome.\u0026rdquo; J Orthop Sci. 2008 Jan;13(1):1\u0026ndash;2.\u003c/li\u003e\n\u003cli\u003eNakamura K, Ogata T. Locomotive Syndrome: Definition and Management. Clin Rev Bone Miner Metab. 2016 May 25;14:56\u0026ndash;67.\u003c/li\u003e\n\u003cli\u003eSeichi A, Hoshino Y, Doi T, Akai M, Tobimatsu Y, Iwaya T. Development of a screening tool for risk of locomotive syndrome in the elderly: the 25-question Geriatric Locomotive Function Scale. J Orthop Sci. 2012 Mar;17(2):163\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eIde K, Yamato Y, Hasegawa T, Yoshida G, Hanada M, Banno T, et al. Implications of the diagnosis of locomotive syndrome stage 3 for long-term care. Osteoporos Sarcopenia. 2024 Jun;10(2):89\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eNakamura M, Hashizume H, Oka H, Okada M, Takakura R, Hisari A, et al. Physical performance measures associated with locomotive syndrome in middle-aged and older Japanese women. J Geriatr Phys Ther. 2015 Oct;38(4):202\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eKobayashi T, Morimoto T, Shumanoe C, Ono R, Otani K, Mawatari M. Relationship between the 25-question Geriatric Locomotive Function Scale and falls: A one-year longitudinal observational study of 1,173 healthy community-dwelling residents aged 65 and older. Cureus. 2024 Nov 3;16(11):e72907.\u003c/li\u003e\n\u003cli\u003eKimura A, Takeshita K, Inoue H, Seichi A, Kawasaki Y, Yoshii T, et al. The 25-question Geriatric Locomotive Function Scale predicts the risk of recurrent falls in postoperative patients with cervical myelopathy. J Orthop Sci. 2018 Jan;23(1):185\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eHirano K, Imagama S, Hasegawa Y, Ito Z, Muramoto A, Ishiguro N. The influence of locomotive syndrome on health-related quality of life in a community-living population. Mod Rheumatol. 2013 Sep;23(5):939\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eYoshimura N, Iidaka T, Horii C, Mure K, Muraki S, Oka H, et al. Epidemiology of locomotive syndrome using updated clinical decision limits: 6-year follow-ups of the ROAD study. J Bone Miner Metab. 2022 Jul;40(4):623\u0026ndash;35.\u003c/li\u003e\n\u003cli\u003eIde K, Yamato Y, Hasegawa T, Yoshida G, Yasuda T, Banno T, et al. Prospective nursing care certification using the 25-question Geriatric Locomotive Function Scale. Geriatr Gerontol Int. 2021 Jun;21(6):492\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eNiwa H, Ojima T, Watanabe Y, Ide K, Yamato Y, Hoshino H, et al. Association between the 25-question Geriatric Locomotive Function Scale score and the incidence of certified need of care in the long-term care insurance system: The TOEI study. J Orthop Sci. 2021 Jul;26(4):672\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eTavares DRB, Santos FC. Locomotive syndrome in the elderly: translation, cultural adaptation, and Brazilian validation of the tool 25-Question Geriatric Locomotive Function Scale. Rev Bras Reumatol Engl Ed. 2017 Jan;57(1):56\u0026ndash;63.\u003c/li\u003e\n\u003cli\u003eYang Y-L, Wang H-H, Su H, Lu H, Yu H, Wang J, et al. Reliability and validity tests of the Chinese version of the Geriatric Locomotive Function Scale (GLFS-25) in tumor survivors. Heliyon. 2024 May 15;10(9):e29604.\u003c/li\u003e\n\u003cli\u003eTaghinejad H, Mohammadyari E, Tavan H, Mohammadyari A. Investigating the validity and reliability of the GLFS-25 questionnaire by factor analysis in the elderly hospitalized at the intensive and cardiac care units. Heliyon. 2023 Jul 11;9(7):e18111.\u003c/li\u003e\n\u003cli\u003eMahali NS, Hosseini MA, Rahgozar M, Tabrizi KN. Evaluation of cultural adaptation, validity and reliability of the questionnaire of Geriatric Locomotive Function Scale-25 questions. Pharmacophore. 2017;8(0\u0026ndash;2017):0\u0026ndash;0.\u003c/li\u003e\n\u003cli\u003eIkemoto T, Inoue M, Nakata M, Miyagawa H, Shimo K, Wakabayashi T, et al. Locomotive syndrome is associated not only with physical capacity but also degree of depression. J Orthop Sci. 2016 May;21(3):361\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eTakenaka H, Ikemoto T, Suzuki J, Inoue M, Arai Y-C, Ushida T, et al. Association between trunk muscle strength, lumbar spine bone mineral density, lumbar scoliosis angle, and skeletal muscle volume and locomotive syndrome in elderly individuals: A dual-energy X-ray absorptiometry study. Spine Surg Relat Res. 2020;4(2):164\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eWang C, Ikemoto T, Hirasawa A, Arai Y-C, Kikuchi S, Deie M. Assessment of locomotive syndrome among older individuals: a confirmatory factor analysis of the 25-question Geriatric Locomotive Function Scale. PeerJ. 2020 Apr 14;8:e9026.\u003c/li\u003e\n\u003cli\u003eBond TG, Fox CM. Applying the Rasch model: Fundamental measurement in the human sciences. J Educ Meas. 2003 Jun;40(2):185\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eMcHorney CA, Monahan PO. Postscript: Applications of Rasch analysis in health care. Med Care. 2004 Jan;42(1 Suppl):I73-8.\u003c/li\u003e\n\u003cli\u003eCourt H, Greenland K, Margrain TH. Measuring patient anxiety in primary care: Rasch analysis of the 6-item Spielberger State Anxiety Scale. Value Health. 2010 Sep;13(6):813\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eKaneda T, Takabatake S, Higashi Y, Horishima Y, Somei Y, Nakaoka K, et al. Evaluation of psychometric properties of the activities of daily living scale of motor function used by caregivers using Rasch analysis. J Phys Ther Sci. 2020 Feb;32(2):148\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eYamada K, Ito YM, Akagi M, Chosa E, Fuji T, Hirano K, et al. Reference values for the locomotive syndrome risk test quantifying mobility of 8681 adults aged 20-89 years: A cross-sectional nationwide study in Japan. J Orthop Sci. 2020 Nov;25(6):1084\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007 Oct 20;335(7624):806\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eGuilleux A, Blanchin M, Hardouin J-B, S\u0026eacute;bille V. Power and sample size determination in the Rasch model: evaluation of the robustness of a numerical method to non-normality of the latent trait. PLoS One. 2014 Jan 10;9(1):e83652.\u003c/li\u003e\n\u003cli\u003eLinacre JM. A user\u0026rsquo;s guide to facets rasch-model computer programs. Available from: https://www.winsteps.com/manuals.htm\u003c/li\u003e\n\u003cli\u003eR Core Team (2023). \u003cem\u003eR: A Language and Environment for Statistical Computing\u003c/em\u003e. R Foundation for Statistical Computing, Vienna, Austria. Available from: https://www.R-project.org/\u003c/li\u003e\n\u003cli\u003ePourbordbari N, Jensen MB, Olesen JL, Holden S, Rathleff MS. Bio-psycho-social characteristics and impact of musculoskeletal pain in one hundred children and adolescents consulting general practice. BMC Prim Care. 2022 Jan 25;23(1):20.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Locomotive Syndrome, Geriatric Locomotive Function Scale (GLFS-25), Rasch Analysis, Musculoskeletal Disorders","lastPublishedDoi":"10.21203/rs.3.rs-6002959/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6002959/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eLocomotive syndrome (LS), a condition characterized by diminished mobility due to musculoskeletal disorders, is a growing concern among older adults. The 25-item Geriatric Locomotive Function Scale (GLFS-25) is a common tool for LS assessment. However, its reliance on classical test theory and the inclusion of non-motor function items raise questions about its accuracy in reflecting motor dysfunction severity. This study aimed to evaluate the GLFS-25's psychometric properties using Rasch analysis, focusing on item difficulty variations between young-old (60\u0026ndash;74 years) and old-old (75\u0026ndash;89 years) individuals with musculoskeletal disorders (MSDs).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis cross-sectional study recruited 1000 outpatients (500 young-old and 500 old-old) with MSDs. Participants completed the GLFS-25. Rasch analysis was performed using Winsteps software to assess item difficulty, person ability, and item fit. Wright person-item maps were generated to visualize the distribution of item difficulty and person ability. Infit and outfit mean-square values were used to identify misfitting items.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe mean age of participants was 73.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 years. Mean GLFS-25 scores were 26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.3 (young-old) and 35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.0 (old-old). Cronbach's alpha exceeded 0.95 in both groups. Significant differences in LS severity proportions were observed between age groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Wright maps revealed a scarcity of items discriminating among low-scoring individuals, particularly in the young-old group. Items related to dressing, toilet use, and bathing were most discriminating for high-scoring individuals. Neck/upper limb pain and social engagement were identified as misfitting items across both age groups. Back/lower back/buttock pain and social interaction were misfitting in the young-old and old-old groups, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhile the GLFS-25 demonstrated excellent internal consistency, Rasch analysis revealed limitations in its ability to discriminate among individuals with low LS scores, particularly in the young-old group. In addition, several misfitting items were identified, suggesting that some items may not contribute effectively to the measurement of LS.\u003c/p\u003e","manuscriptTitle":"Rasch Analysis of the 25-Question Geriatric Locomotive Function Scale in Japanese Older Adults with Musculoskeletal Disorders: Identifying Age-Related Differences in Item Difficulty and Misfitting Items","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-14 10:26:38","doi":"10.21203/rs.3.rs-6002959/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a419d793-731f-4887-91f0-06892ff9d9cd","owner":[],"postedDate":"February 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-13T18:23:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-14 10:26:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6002959","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6002959","identity":"rs-6002959","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}