ArticleBMJ open2023
Association between daily life walking speed and frailty measured by a smartphone application: a cross-sectional study.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Trial
- Mild cognitive impairment has a direct effect on gait speed even when accounting for frailty.BMC geriatrics · 2026Article
- Validity of Smartphone-Based Measurement for Assessing Lower Limb Power for Sarcopenia and Frailty Discrimination: Cross-Sectional Study.JMIR formative research · 2026Article
- Comparability of Daily-Life Walking Speed Measured by Smartphone GPS and Ankle-Band Accelerometer: Cross-Sectional Study.JMIR formative research · 2025Article
- Physical Frailty Prediction Using Cane Usage Characteristics during Walking.Sensors (Basel, Switzerland) · 2024Article
- Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review.Geriatrics (Basel, Switzerland) · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo assess whether frailty can be assessed using a smartphone and whether daily walking speed (DWS) is associated with frailty.
designCross-sectional study.
settingThree prefectures (Kanagawa, Saitama and Tokyo) in Japan.
participantsThe study enrolled 163 participants (65 in the robust group, 69 in the prefrailty group and 29 in the frailty group) by sending letters to house owners aged≥55 years. PRIMARY AND SECONDARY OUTCOME MEASURES: The participants downloaded the DWS measurement application on their smartphones, which measured the daily walking (DW) parameters (DWS, step length and cadence) and the Kihon checklist for frailty assessment. The differences in the DW parameters between the robust, prefrailty and frailty groups were examined using one-way analysis of variance. We conducted logistic regression analysis for the Crude model (each DW parameter), model 1 (adjusted for the number of steps) and model 2 (model 1+age, sex and the number of chronic diseases).
resultsDWS was marginally significantly slower in the frailty group than in the prefrailty and robust group (robust 1.26 m/s vs prefrailty 1.25 m/s vs frailty 1.19 m/s, p=0.060). Step length was significantly smaller in the frailty group than in the robust group (robust 66.1 cm vs prefrailty 65.9 vs frailty 62.3 cm, p<0.01). Logistic regression analysis for the three models revealed that DWS was significantly associated with frailty.
conclusionsDWS measured using the smartphone application was associated with frailty. This was probably due to the shorter step length and body height seen in frail individuals.
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