This single-centre, cross-sectional diagnostic study will determine whether the new self-completed Self-Assessment for Falls in the Elderly (SAFE) questionnaire can classify fall-risk level (low, moderate, high) in adults ≥ 60 years as accurately as the current clinician-administered international algorithm that mixes yes/no questions with physical tests; to do so, about 300 participants will (1) sign consent, (2) answer the 5-minute SAFE, and (3) undergo guideline assessment and tests by a clinician in the same visit, after which researchers will compare SAFE and clinician results for sensitivity, specificity, and predictive values, examine agreement and correlations, and give immediate risk-based prevention advice:
* Eligibility: men or women ≥ 60 y, stable walking/balance ≥ 1 month, able to read French and perform brief tests; legal guardianship or refusal excludes. * Participant tasks: complete SAFE; perform Timed Up-and-Go, 4 m gait speed, Five-Times-Sit-to-Stand and Short Physical Performance Battery (SPPB) under supervision * Benefits/Risks: instant personalised fall-risk feedback; SAFE is risk-free and physical tests carry only minimal supervised exertion.
Falls are a leading cause of injury and death in older adults, and current assessments require trained staff; if SAFE proves equivalent, it could enable large-scale, low-cost self-screening and support future digital monitoring tools for fall prevention.
People aged 60 or over, judged by the investigator to be in stable clinical condition as regards walking and balance for at least one month,
Able to perform the necessary physical assessments
Unable, according to the investigator, to answer a self-questionnaire,
Patient's refusal to take part in the study
Absence of a caregiver if the participant is unable to answer the questionnaire alone
Unable to understand the information note
Single group
Questionnaire and Physical Exam
Diagnostic testNext, the risk of falling will be assessed by a healthcare professional using a hetero-questionnaire and physical tests, as proposed in the algorithm for global recommendations (routine care). These tests include a detailed characterisation of the history of falls, the Timed Up and Go, the Five Times Sit to Stand, the 4 m walking speed and the Short Physical Performance Battery.
Safe Self-Administered Questionnaire
Diagnostic testAll people who agree to take part in the study will first complete the SAFE self-questionnaire (intervention). the Self Assessment for Falls in the Elderly (SAFE), an auto-questionnaire that converts the binary items and performance tests of the 2022 World Guidelines for Falls Prevention and Management into visual analogue scales (100 mm each).
Performance of the SAFE Self-Assessment Questionnaire compared with the global recommendations algorithm (Hetero-administered questionnaire and physical tests). sensitivity
Based on predefined VAS thresholds in the self-questionnaire, we apply the global recommendations algorithm to classify patients into low, moderate, and high risk of falling: High Risk: At least one of the following: Two or more falls in the last year. One fall with injury in the last year. One fall with inability to get up in the last year. Unexplained fall in the last year. Frailty: At least three of the five Fried factors (fatigue, \>5 seconds for 4 meters, \>15 seconds for 5 chair lifts, \>4.5 kg weight loss in one year, sedentary lifestyle). Moderate Risk: Non-severe fall, fear of falling, or instability while walking/standing, associated with: TUG ≥ 15 seconds, or ≥ 5 seconds to walk 4 meters. Low Risk: One non-severe fall, fear of falling, or instability, but no frailty and normal TUG (Timed Up and Go) and walking speed. We compare the statistical performance of SAFE with the reference standard using contingency tables, reporting sensitivity
Performance of the SAFE Self-Assessment Questionnaire compared with the global recommendations algorithm (Hetero-administered questionnaire and physical tests). specificity
Based on predefined VAS thresholds in the self-questionnaire, we apply the global recommendations algorithm to classify patients into low, moderate, and high risk of falling: High Risk: At least one of the following: Two or more falls in the last year. One fall with injury in the last year. One fall with inability to get up in the last year. Unexplained fall in the last year. Frailty: At least three of the five Fried factors (fatigue, \>5 seconds for 4 meters, \>15 seconds for 5 chair lifts, \>4.5 kg weight loss in one year, sedentary lifestyle). Moderate Risk: Non-severe fall, fear of falling, or instability while walking/standing, associated with: TUG ≥ 15 seconds, or ≥ 5 seconds to walk 4 meters. Low Risk: One non-severe fall, fear of falling, or instability, but no frailty and normal TUG and walking speed. We compare the statistical performance of SAFE with the reference standard using contingency tables, reporting specificity
Performance of the SAFE Self-Assessment Questionnaire compared with the global recommendations algorithm (Hetero-administered questionnaire and physical tests). positive predictive values
Based on predefined VAS thresholds in the self-questionnaire, we apply the global recommendations algorithm to classify patients into low, moderate, and high risk of falling: High Risk: At least one of the following: Two or more falls in the last year. One fall with injury in the last year. One fall with inability to get up in the last year. Unexplained fall in the last year. Frailty: At least three of the five Fried factors (fatigue, \>5 seconds for 4 meters, \>15 seconds for 5 chair lifts, \>4.5 kg weight loss in one year, sedentary lifestyle). Moderate Risk: Non-severe fall, fear of falling, or instability while walking/standing, associated with: TUG ≥ 15 seconds, or ≥ 5 seconds to walk 4 meters. Low Risk: One non-severe fall, fear of falling, or instability, but no frailty and normal TUG and walking speed. We compare the statistical performance of SAFE with the reference standard using contingency tables, reporting positive predictive values,
Performance of the SAFE Self-Assessment Questionnaire compared with the global recommendations algorithm (Hetero-administered questionnaire and physical tests). negative predictive values
Based on predefined VAS thresholds in the self-questionnaire, we apply the global recommendations algorithm to classify patients into low, moderate, and high risk of falling: High Risk: At least one of the following: Two or more falls in the last year. One fall with injury in the last year. One fall with inability to get up in the last year. Unexplained fall in the last year. Frailty: At least three of the five Fried factors (fatigue, \>5 seconds for 4 meters, \>15 seconds for 5 chair lifts, \>4.5 kg weight loss in one year, sedentary lifestyle). Moderate Risk: Non-severe fall, fear of falling, or instability while walking/standing, associated with: TUG ≥ 15 seconds, or ≥ 5 seconds to walk 4 meters. Low Risk: One non-severe fall, fear of falling, or instability, but no frailty and normal TUG and walking speed. We compare the statistical performance of SAFE with the reference standard using contingency tables, reporting negative predictive values
VAS thresholds for the self-questionnaire
In this section, for each binary question on the hetero-questionnaire or involving a physical test, we aim to determine a VAS threshold from the self-questionnaire for the corresponding question. The hetero-questionnaire measure is used as a reference measure: fear of falling, unsteadiness when standing up, unsteadiness when walking, getting up easily from a chair without using hands, walking speed, fatigue, reduction in physical activity.
Concordance analyses
We wish to evaluate the concordance between the SAFE self-questionnaire responses and the global recommendations algorithm hetero-assessment via the Gwet coefficient for qualitative variables and the intra-class correlation coefficient (ICC) for quantitative variables.
Point-biserial correlations
We wish to evaluate the correlation between the VAS of the self-questionnaire and the dichotomous variables of the hetero-questionnaire (point-biserial correlations).
Pearson correlation analysis
We wish to evaluate the correlation between the VAS of the self-questionnaire and the physical tests of the hetero-questionnaire (Pearson correlations).
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