Table 2.
Validity and reliability of the questionnaires included in the review.
| Tool name | Study | AUC | Sensitivity | Specificity | Cronbach’s α | ICC | Correlation with other tools (r) | Other parameters |
|---|---|---|---|---|---|---|---|---|
| Scripted Fall Risk Screening Tool (FRST) | Feilding et al, 2013[16] | 0.869 | 0.830 (inter-rater) | |||||
| Modified Suzuki’s fall assessment Questionnaire (FRAS) | Hirase et al, 2014[35] | 0.73 (0.62,0.83) for the 7 factors | 84% | 68% | ||||
| Questionnaire from NHATS study | Gadkaree et al, 2015[25] | Any fall 0.69 (95% CI = [0.67, 0.71])Recurrent falls 0.77 (95% CI = [0.74, 0.79]) | ||||||
| Frailty Index (FI) | Kojima et al, 2015[26] | 0.62 (95 % CI[0.53, 0.71]) | 31.6% | 85.9% | OR = 3.04, (95 % CI = [1.53,6.02]) | |||
| NA, Online Questionnaire | Obrist et al, 2016[27] | 0.67 (95% CI = [0.54, 0.81] | ||||||
| ABC | Cleary et at, 2017[28] | 0.973* | 0.879* (95% CI = [0.779, 0.934]) (test-retest) | OR = 0.95 | ||||
| Self-reported unsteadiness | Donoghue et al, 2017[29] | IRR = 1.53 (0.93, 2.49) | ||||||
| 3-STEADI (3 key questions) vs Stay Independent | Eckstrom et al, 2017[24] | **0.981 (SE=0.021) | 100%** | 83.3%** | 0.746** (Stay Independent) | 95% of high-risk (with 12-Item Stay Independent) were identified with 3-STEADI | ||
| NA | Rodriguez et al, 2017[30] | 0.74 (95% CI = [0.66, 0.82]) | 70% | 72% | ||||
| Online Assessment Instrument for Elderly Falls (IAQI) | Silveira et al, 2018[17] | CVC = 0.76 (clarity), CVC = 0.82 (content) | ||||||
| FRRISque | Chini et al, 2019[18] | 91.3% | 73.4% | |||||
| Thai-modified STEADI | Loonlawong et al, 2019[19] | 0.78 (12 and 18-Item) | 0.95 (12-Item) 0.91 (18-Item) | r = 0.330 (TUG), r = -0.499 (BBS) – 12-Item r = 0.358 (TUG), r = -0.484 (BBS) – 18-Item | ||||
| Chinese HomeFAST | Lai et al, 2020[32] | 83% | 96% | 0.94 | 0.89 (95% C.I. = [0.84, 0.93]) (inter-rater) 0.88 (95% C.I. = [0.90, 0.94]) (test-retest) | |||
| Persian Fall Risk Screening Tool (FRST) | Tabatabaei et al, 2020[20] | 0.73 | r = 0.122 (TUG) | CVI = 0.87 | ||||
| MFES (modified falls efficacy scale) | Yang et al, 2020[31] | 0.95*** | 0.93 (test-retest)*** | IRR = 0.96 | ||||
| Brazil HomeFAST | Ferreira et al, 2021[21] | 0.83 (95% CI = [0.70,0.90]) (inter-rater) 0.85 (95% CI = [0.74,0.91]) (intra-rater) | ||||||
| LRMS | Argyrou et al, 2022[22] | 0.930 (95% CI= [0.88, 0.98]) | 93% | 91% | 0.807 | 0.991 (test-retest) | r = 0.831 (TUG), r = –0.820 FES-I, r = –0.812 (Tinetti balance), r = –0.789 (Tinetti gait), r = –0.562 (GDS-15) | |
| 3-STEADI (3 key questions) | Burns et al, 2022[33] | 68.7% | 57.9% | OR = 3 (95% CI = [2.3, 4.1]) | ||||
| Stay Independent | 55.7% | 75.9% | OR = 3.9 (95% CI = [2.9, 5.3]) | |||||
| AGS/BGS | 60.1% | 66.4% | OR = 3 (95% CI = [2.2, 4]) | |||||
| Short FES-I | 22.5% | 89.4% | OR = 2.5 (95% CI = [1.6, 3.8]) | |||||
| Fell in the past year | 40.3% | 86.2% | OR = 4.2 (95% CI = [3.1, 5.8]) | |||||
| Fallen in the past 12months | 45.3% | 83.4% | OR = 4.2 (95% CI = [3, 5.7]) | |||||
| Machine learning | Ikeda et al, 2022[34] | 0.88 (SD=0.02) | ||||||
| FRSAS (Fall Risk Self Assessment Scale) | Wang et al, 2022[23] | 0.757 | 0.967 (test-retest) |
AUC = area under the receiver operating characteristic curve, ICC = intraclass correlation coefficient, α = Cronbach’s alpha coefficient, r = Spearman’s correlation coefficient, CI = confidence interval, IRR = incident rate ratio, OR = odds ratio, CVC = content validity coefficient, CVI = content validity index.
*
from Cleary et al.[43];
**
from Rubenstein et al.[38];
***
from Hill et al.[44]