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Balance Disorders: 

(Godi, et al, 2013; n = 93 patients with balance disorders, mean age = 66.2(13.2) years, 53 female/40 male, Dx: n = 3 Parkinson¡¯s, n = 25 hemiplegia, n = 6 MS, n = 5 vestibular disorders, n = 4 neoplasm CNS, n = 6 neuromuscular disease, n = 8 hereditary ataxia, n = 8 poly neuropathy, n = 6 age-related balance disorders) 

• SEM = 1.26 (1.01-1.65)

Balance Disorders: 

(Godi,et al, 2013) 

• Clinically meaningful change is improvement of 4 points (out of 28 total)

Balance Disorders:

(Godi, et al, 2013; n = 32 patients with balance disorders, mean age = 67.3 (13.5) years, 19 female/13male, Dx: n = 8 Parkinson¡¯s, n = 7 hemiplegia, n = 3 vestibular disorders, n = 4 age-related balance disorders, 10 with ¡°other neuro" Dx) 

• Test-retest 1 to 3 days after baseline assessment. Excellent test-retest reliability ICC = 0.96 (0.94-0.99) 

Balance Disorders:  

(Godi, et al., 2013; n = 32 patients, sample per above) 

• Excellent interrater reliability ICC = 0.98 (0.97-0.99) 

Balance Disorders:

(Franchignoni, et al. 2010; n = 115, mean age = 62.7 (16) years, 62 female/53 male, Dx: n = 21 Parkinson¡¯s, n = 15 neuromuscular disease, n = 14 hereditary ataxia, n = 11 MS, n = 22 hemiparesis, n = 7 peripheral vestibular disorders, n = 6 TBI, n = 10 nonspecific age-related balance disorders, n = 3 encephalopathy, n = 3 cervical myelopathy, n = 2 CNS neoplasm) 

• Factor and Rasch analysis performed to identify optimal test psychometrics for item selection for Mini BESTest. High item separation reliability r = 0.98, Item separation index = 7.35, and Person separation reliability = 0.86 without item redundancy. 

(Godi, et al., 2013; n = 93 patients with balance disorders, mean age = 66.2 (13.2)years, 53 female/40male, Dx: n = 3 Parkinson¡¯s, n = 25 hemiplegia, n = 6 MS, n = 5 vestibular disorders, n = 4 neoplasm CNS, n = 6 neuromuscular disease, n = 8 hereditary ataxia, n = 8 poly neuropathy, n = 6 age-related balance disorders} 

• Excellent internal consistency at baseline testing and follow-up assessment: Cronbach alpha = 0.90 and 0.91 respectively

Balance Disorders:

(Godi, et al., 2013) 

• Excellent concurrent validity of Mini-BESTest with Berg Balance Scale r = 0.85 (CI 0.78-0.90); 
• Excellent validity between Mini-BESTest and mean global rating of change score in rehabilitation r = 0.72 (CI 0.61-0.81)

Adult with Balance Deficits

(Franchignoni, et al., 2010) 

• Internal construct validity supported based on hierarchy of item difficulty (Rasch analysis. Item difficulty ranged from -4 to +2.5 logits)

Adults with Balance Deficits

(Franchignoni, et al., 2010; n = 115 with diverse neurological diagnoses, 53 men, mean age 62.7 ¡À 16 years, diagnoses included hemiparesis, Parkinson disease, neuromuscular diseases, hereditary ataxia, multiple sclerosis, peripheral vestibular disorders, traumatic brain injury, cervical myelopathy) 

• High content validity since individual items are part of well know balance batteries, such as Berg Balance Scale, Clinical Test of Sensory Integration in Balance, Dynamic Gait Index and TUG. 
• Factor analysis selected 24 out of the 36 original BESTest items likely to represent dynamic balance; Rasch analysis was used to improve rating categories and to delete 10 items that were misfitting or showed local dependency.  The model was verified using confirmatory factor analysis

• Supported based on balance performance items that examine the construct of dynamic balance.

Balance Disorders:

(Godi, et al., 2013) 

• No evidence of floor or ceiling effect in mixed neurologic cohort at baseline mean score = 12.8 (6.9); or after treatment in rehabilitation center mean score = 15.8 (6.9); 2 participants (2.1%) reached Mini BESTest top score.

Balance Disorders : 

(Godi, et al., 2012; n = 93 patients with balance disorders) 

• Subjects had 10 physical therapy treatment sessions for balance disorders. 
• SEM = 1.26 (1.01-1.65); MDC = 3.5 ; MCID = 4 pts; Out of 40 subjects who global rating of change was > 3 (moderate to large improvement) 38/40 (95%) showed Mini-BESTest changes score > 4 pts 
• Excellent ability to identify those subjects with clinically meaningful improvement: AUC = 0.92 (0.84-0.97), sensitivity = 94%, specificity = 81%, discriminative accuracy to detect moderate improvement in balance = 79%
• Discriminatory accuracy excellent, area under ROC curve 0.92, to determine a moderate to large global rating of change improvement.

Chronic Stroke 

(Tsang et al 2013, n = 106 people with stroke, mean age 57.1 ¡À 11.0 years, 73 men, 33 women and 48 controls, mean age 60.2 ¡À 9.3 years, 28 men and 20 women)

• Scores of ¡Ü 17.5 identified those with a history of falling, sensitivity 64%, specificity 64% AUC 0.64

Chronic Stroke

(Tsang et al, 2013)

• Excellent for total score ICC = 0.96, Poor to excellent reliability for individual items kappa = 0.37 to 1.0

Chronic Stroke 

(Tsang et al 2013)

• Excellent for total scores ICC = 0.96, poor to excellent reliability for individual items kappa = 0.36 to 1.0

Chronic Stroke 

(Tsang et al 2013)

• Excellent Cronbach¡¯s alpha = 0.89, 0.93, 0.94 for each rater

Chronic Stroke

(Tsang et al 2013) 

• Excellent correlation with Berg Balance Scale r = 0.83
• Adequate correlation with Functional reach test r = 0.55
• Excellent correlation with one leg stand on paretic side r = 0.83
• Adequate correlation with one leg stand on non-paretic side r = 0.54
• Excellent correlation with Timed ¡°Up & Go¡± r = -0.82

(Bergstrom et al 2012, n = 9, mean age 78.4 years, range 66-90 years, median 17 months post CVA.  Swedish version)

• Excellent correlation with Berg Balance Scale r = 0.94
• Excellent correlation with Timed ¡°Up & Go¡± r = -0.89

Chronic Stroke 

(Tsang et al 2013)

• The mini-BESTest discriminates between those with a history of stroke and healthy control subjects (p < 0.001)
• The mini-BESTest discriminates between subjects with chronic stroke with and without a history of falling (p = 0.03)

Chronic Stroke 

(Tsang et al 2013)

• Skewness = - 0.81
• Floor effect: 0 participants with lowest score
• Ceiling effect: 0.9% participants with highest score

Parkinson¡¯s Disease: 

(Leddy et al, 2011, subset of 24 subjects, MDS-UPDRS = 71 ¡À 21.9, disease duration = 6.9 ¡À 3.38; Hoehn and Yahr stage 1 ¨C 2 participants, stage 2 ¨C 11 participants, stage 2.5 ¨C 6 participants, stage 3 ¨C 3 participants, stage 4 ¨C 2 participants, 21% were classified as fallers.)

• SEM calculated = 6.16% or 1.99 points

Parkinson¡¯s Disease: 

(Leddy et al, 2011)

• MDC calculated = 17.1% or 5.52 points

Parkinson¡¯s Disease:

(Leddy, et al, 2011; total sample n = 80, mean age = 68.2 (9.3)years, mean H & Y = 2.4 (0.64), 31% were fallers) 

• Preferred Fall risk cut score 63% (20/32 points total) had adequate ability to identify fallers (sensitivity = 0.88, specificity = 0.78). To maximize sensitivity and LR-, a cut score of 72% (23/32) was identified (sensitivity = 0.96, specificity = 0.47) 

(Duncan, Leddy, & Earhart, 2013; n =56 with idiopathic PD, mean age = 69.5 years, 32 male/23 female, H&Y stage (2 = 21, 2.5 = 25, 3 = 9, 4 = 1) mean stage 2.4 (0.5)) 

• Using a cut score of 16/32 points, the Mini-BESTest demonstrated adequate ability to predict 6-month prospective fallers (AUC = 0.80, sensitivity = 0.75, specificity = 0.79, LR+ = 3.57, LR- = 0.32). Mini-BESTest was superior to gait measures to detect fall risk in PD cohort. 

(Duncan,et al, 2012; Baseline n = 80 PD, Six-month evaluation n = 51, mean age = 67.5 (8.8), years post diagnosis 7.7(3.9), H & Y stage 2.4 (0.6), UPDRS 37.8 (13.1), 27% fallers; 12-month evaluation n = 40, mean age 67.3 (9.5), years post diagnosis 7.2 (4.1), H&Y stage 2.3 (0.6), UPDRS 39.3 (13.3), 37% fallers) 

Based on a Cut Score < 20/32 points total (63%); 

• Adequate ability to predict fallers at 6 month prospectively (AUC = 0.87, sensitivity = 0.86, specificity = 0.78, LR+ = 3.97, LR- = 0.18) 
• Adequate ability to predict fallers at 12 months prospectively (AUC = 0.77, sensitivity = 0.62, specificity = 0.74, LR+ = 2.37, LR- = 0.52) 

(Duncan, et al, 2013; n = 80 with idiopathic PD, mean age = 68.2 (9.7), mean MDS-UPDRS 41.3 (14.7), H & Y stage [1 = 4, 2 = 27, 2.5 = 30, 3= 13, 4= 6]) 

Based on a recommended Cut score < 20/32 points to detect fallers: 

• Adequate ability to identify fallers based on retrospective fall report (AUC = 0.86, sensitivity = 0.88, specificity = 0.78, LR+ = 4.03, LR- = 0.15} 
• Adequate ability to predictive fallers based on 6 ¨Cmonth prospective falls (AUC = 0.87, sensitivity = 0.86, specificity = 0.78, LR+ = 3.97, LR- = 0.18); and for 12 month prospective falls (AUC = 0.77, sensitivity = 0.62, specificity = 0.74, LR+ = 2.37, LR- = 0.52) 

(Mak and Auyeung 2013, n = 110, non-recurrent fallers n=86, 34 female, mean age 63.5¡À 9.3; recurrent fallers n=24, 10 female, mean age 62.2 ¡À 7.5)

• Scores of ¡Ü 19 identified recurrent fallers; sensitivity 79%, specificity 67% AUC 0.75

(King et al 2012)

• Scores of ¡Ü 21 differentiate those with and without postural response deficits with a sensitivity of 89%, specificity 81%

Parkinson¡¯s Disease:

(Leddy et al, 2011; subset of subjects n = 24, MDS-UPDRS = 71 (21.9), disease duration mean 6.9 (3.38), 21% fallers; H & Y stages [1 = 2, 2 = 11, 2.5 = 6, 3 = 3, 4 = 2], 21% n = 5 fallers) 

• Excellent test retest reliability (ICC = 0.92)

Parkinson¡¯s Disease:

(Leddy, et al., 2011; subset of subjects, n = 15 MDS-UPDRS = 74.2 (18.6), disease duration = 6.8 years (3.26), H & Y stages (1 = 2, 2 = 7, 2.5 = 3, 3 = 2, 4 = 1), 20% fallers) 

• Excellent Inter-rater reliability (ICC = 0.91)

Parkinson's Disease:

(King, et al., 2012; n = 97, mean age 65.6 (7.1, time since diagnosis mean = 6.5 (5), H & Y mean = 2.3 (0.6) stages 1-4, UPDRS mean = 31.6 (11.2), 59 male/38 female.) 

• Excellent concurrent validity between Mini-BESTest and Berg (r = 0.79); 
• Adequate correlation between Mini-BESTest and UPDRS-disease severity (r = -0.51). 

(Leddy, et al., 2011; total sample n = 80, mean age = 68.2 (9.3) years, mean H & Y = 2.4 (0.64), 31% were fallers) 

• Mini-BESTest has excellent correlation with BESTest (r = 0.955) 

(Duncan, et al., 2013; n = 80 with idiopathic PD, mean age = 68.2 (9.7), mean MDS-UPDRS 41.3 (14.7), H & Y stage [1 = 4, 2 = 27, 2.5 = 30, 3 = 13, 4 = 6]) 

• Excellent concurrent validity between the Mini-BESTest and Brief BESTest (r = 0.94) 

(McNeely, et al., 2012; n = 22, mean age = 71.3 (7.6), 13 male/9 female, MMSE mean 28 (1.8), disease duration mean 7.0 (4.2) years, mean MED_UPDRS = 39.1 (9.2) off meds, 25.3 (6.9) on meds, mean H & Y stage 2.2 (0.3) 

• Excellent concurrent validity between Mini-BESTest and Berg Balance Scale (r = 0.83); 
• Adequate correlation between Mini-BESTest and Activity Specific Balance Confidence Scale ABC (r = 0.66). 

(McNeely, et al., 2011; n = 23 mean age = 62 (9), mean disease duration = 15 (6) years) 

• Adequate correlation between Mini-BESTest scores and UPDRS postural stability item (item 3.12) (r = -0.44), p < 0.001

(Duncan, et al., 2013; total n = 53, Off meds group n = 28: mean age = 70 (7.4) years, 15 males/13 females, H &Y stage 2 = 8, 2.5 = 15, 3 = 5, 3 fallers & 5 gait freezers; On meds group n = 53, mean age = 68 (8.5) years, 31 males/22 females, H&Y 1 = 2, 2 = 28, 2.5 = 16, 3 = 2, 4 = 5, 11 fallers and 17 gait freezers) 

• Excellent concurrent validity between Mini-BESTest and Four square step test (r = -0.65) p < 0.001  
• Mini-Best had adequate predictive validity to discriminate fallers and nonfallers with PD (AUC = 0.80, sensitivity = 0.88, specificity = 0.78); superior to 4SSS for identifying fall risk in PD. 

(Duncan, Leddy & Earhart, 2011; n = 80 with idiopathic PD, H & Y stages I-IV, age > 40 years, no details on sample) 

• Excellent correlation between Mini-BESTest and Five times sit to stand test (r = -0.71 p < 0.001)
• Multiple regression revealed that Mini-BESTest and Nine Hole peg test explained 53% of variance in FTSTS

(Bergstrom et al 2012, n = 9 with mild to moderate Parkinson disease, mean age 60.3 years, age range 46-85 years, 8 female, Hoehn and Yahr stages I-III)

• Excellent correlation with  Berg Balance Scale r = 0.94
• Excellent correlation with Timed ¡°Up & Go¡± r = -0.81
• Poor correlation with Falls Efficacy Scale r = 0.26

(Mak and Auyeung 2013)

• The mini-BESTest score was a significant predictor of recurrent falls using multivariate logistic regression.

Parkinson¡¯s Disease:

(Leddy, et al., 2011; total sample n = 80, mean age = 68.2 (9.3) years, mean H & Y = 2.4 (0.64), 31% were fallers) 

• Significant difference between mean Mini BESTest score of fallers= 14.3 (6.2) and nonfallers = 22.9 (5.5) in PD cohort (average difference between groups of 27%)
• Total mini-BESTest scores discriminated between fallers and non-fallers AUC = 0.86
• No specific section of the BESTest or mini-BESTest captured the primary balance deficit

(King, et al., 2012; n = 97 see above) 

• Excellent ability to detect those PD patients with balance deficits based on H & Y stages 1 - 2 versus 3 - 4; AUC = 0.91; Cut off score to distinguish those with and without balance deficits < 21/28 total pts (sensitivity = 89%, specificity = 81%) Mini- BESTest was superior to Berg in discriminating disease severity in PD cohort based on H & Y stage.

Parkinson's Disease

(King, et al., 2012; n = 97, see above) 

• No evidence of ceiling effect, normal distribution of scores in PD cohort with varied H&Y stages, disease severity.
• Skewness -0.93 

(McNeely, et al., 2012; n = 22, see above) 

• No ceiling effect was seen in Mini BESTest scores for PD cohort as compared to ceiling effect seen in Berg scores.

(Bergstom et al., 2012)

• no subjects scored the maximum or minimu on the mini-BESTest