{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T15:10:25Z","timestamp":1790176225521,"version":"4.1.0"},"reference-count":25,"publisher":"International Journal of Sports Physical Therapy","issue":"11","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:sec id=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Foot strike patterns during running are typically categorized into two types: non-rearfoot strike (NRFS) and rearfoot strike (RFS), or as three distinct types: forefoot strike (FFS), midfoot strike (MFS), and RFS, based on which part of the foot lands first. Various methods, including two-dimensional (2D) visual-based methods and three-dimensional (3D) motion capture-based methods utilizing parameters such as the strike index (SI) or strike angle (SA), have been employed to assess these patterns. However, the consistency between the results obtained from each method remains debatable.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"hypothesispurpose\">\n                    <jats:title>Hypothesis\/Purpose<\/jats:title>\n                    <jats:p>The purpose of this study was to examine the agreement for assessing foot strike patterns into two (NRFS and RFS) or three types (FFS, MFS, and RFS) between 2D visual- and 3D motion capture-based methods. The authors hypothesized that using two description types (NRFS and RFS) would have high inter-method reliability; however, using three description types (FFS, MFS and RFS) would have lower inter-method reliability because of the difficulty in distinguishing between FFS and MFS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"study-design\">\n                    <jats:title>Study design<\/jats:title>\n                    <jats:p>Controlled Laboratory Study<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Overall, 162 foot strikes from four healthy runners with various foot strike patterns were analyzed. Running kinematics and kinetics were recorded using a 3D motion capture system with a force platform. Each foot strike was filmed at 240 fps from the sagittal perspective. The visual, SI, and SA methods were used, and the kappa values for each method were calculated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>An assessment of the two types of foot strike: NRFS and RFS, revealed almost perfect kappa values (\u03ba = 0.89\u20130.95) among the visual, SI, and SA methods. In contrast, an assessment of the three types: FFS, MFS, and RFS, revealed relatively low kappa values (\u03ba = 0.58\u20130.71). Kappa values within the NRFS category, which includes MFS and FFS, ranged from fair to slight (\u03ba = 0.08\u20130.33).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"conclusion\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Previous laboratory findings that categorized foot strike patterns into two distinct types may be applied in observational studies, clinical practice, and training situations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"level-of-evidence\">\n                    <jats:title>Level of evidence<\/jats:title>\n                    <jats:p>Level 2<\/jats:p>\n                  <\/jats:sec>","DOI":"10.26603\/001c.123952","type":"journal-article","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T14:03:49Z","timestamp":1730556229000},"source":"Crossref","is-referenced-by-count":2,"title":["Agreement between 2D Visual- and 3D Motion Capture-based Assessment of Foot Strike Pattern"],"prefix":"10.26603","volume":"19","author":[{"given":"Haruhiko","family":"Goto","sequence":"first","affiliation":[{"name":"Japan Institute of Sports Sciences","department":["Department of Sports Sciences"]},{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University","department":["Graduate School of Sport Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshinao","family":"Kamikubo","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University","department":["Graduate School of Sport Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryota","family":"Yamamoto","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University","department":["Graduate School of Sport Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshiharu","family":"Tsutsui","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University","department":["Faculty of Sport Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suguru","family":"Torii","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ntfnx83","id-type":"ROR","asserted-by":"publisher"}],"name":"Waseda University","department":["Faculty of Sport Sciences"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"11140","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"issue":"2","key":"ref1","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1080\/15438627.2021.1954516","article-title":"Footstrike angle cut-off values to classify footstrike pattern in runners","volume":"31","author":"S. 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