Postural Assessment Scale for Stroke Patients (PASS)

Purpose

The Postural Assessment Scale for StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. Patients (PASS) assesses balance in lying, sitting and standing positions. It was designed specifically for patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and is suitable for all individuals regardless of postural performance.

In-Depth Review

Purpose of the measure

The Postural Assessment Scale for StrokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. Patients (PASS) is comprised of 12 items of increasing difficulty that measure balance in lying, sitting and standing. It was designed specifically for patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain., regardless of postural competence (Barros de Oliveira et al., 2008; Mao et al., 2002). The PASS measures the patient’s ability to maintain stable postures as well as equilibrium in changes of position (Di Monaco et al., 2010). It includes items not assessed by the Berg Balance Scale (Blum & Korner-Bitensky, 2008) and demonstrates better psychometric properties than the Berg Balance Scale and the Fugl-Meyer Assessment modified balance subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
(Mao et al., 2002).

Available versions

The PASS was developed in 1999 by Benaim et al. as an adaptation of the Fugl-Meyer Assessment balance subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
(Benaim et al., 1999). It was originally developed in French and has since been translated into English and Swedish (SwePASS). Short forms of the PASS, with fewer items (5-item SFPASS) and/or smaller scoring scales (PASS-3P), have also been developed.

Features of the measure

Items:

The PASS consists of 12 items of graded difficulty:

Maintaining a posture

• Sitting without support (sitting on the edge of a 50cm-high examination table with feet touching the floor)
• Standing with support (feet position free, no other constraints)
• Standing without support (feet position free, no other constraints)
• Standing on nonparetic leg (no other constraints)
• Standing on paretic leg (no other constraints)

Changing Posture

• Supine to affected side lateral
• Supine to nonaffected side lateral
• Supine to sitting up on edge of table
• Sitting on edge of table to supine
• Sit-to-stand (without any support, no other constraints)
• Stand-to-sit (without any support, no other constraints)
• Standing, picking up a pencil from the floor (without any support, no other constraints) (Barros de Oliveira et al., 2008)

Scoring:

The PASS consists of a 4-point scale where items are scored from 0 – 3. The total score ranges from 0 – 36 (Barros de Oliveira et al., 2008).

Item 1: Sitting without support

• 0 = cannot sit
• 1 = can sit with slight support (e.g. by 1 hand)
• 2 = can sit for more than 10 seconds without support
• 3 = can sit for 5 minutes without support

Item 2: Standing with support

• 0 = cannot stand, even with support
• 1 = can stand with strong support of 2 people
• 2 = can stand with moderate support of 1 person
• 3 = can stand with support on only 1 hand

Item 3: Standing without support

• 0 = cannot stand without support
• 1 = can stand without support for 10 seconds or leans heavily on 1 leg
• 2 = can stand without support for 1 minute or stands slightly asymmetrically
• 3 = can stand without support for more than 1 minute and at the same time perform arm movements above the shoulder level

Items 4 and 5: Standing on the nonparetic / paretic leg

• 0 = cannot stand on the leg
• 1 = can stand on the leg for a few seconds
• 2 = can stand on the leg for more than 5 seconds
• 3 = can stand on the leg for more than 10 seconds

Items 6 – 10

• 0 = cannot perform the activity
• 1 = can perform the activity with much help
• 2 = can perform the activity with little help
• 3 = can perform the activity without help

Description of tasks:

Items are graded by difficulty, whereby lying and sitting items are easier than standing items. Items 6 (supine to the affected side lateral) and 7 (supine to nonaffected side lateral) are the easiest items; item 5 (standing on the paretic leg) is the most difficult item of the assessment (Benaim et al., 1999).

Time:

The PASS takes 1 to 10 minutes to administer (Benaim et al., 1999).

Training requirements:

No special training is required, although clinicians should have an understanding of balance impairment and related safety issues following strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain..

Chien et al. (2007b) note that the different scoring criteria for several items of the PASS may pose difficulties for less-trained assessors, and recommends the simpler SFPASS as an alternative.

Equipment:

• 50cm-high examination table (e.g. Bobath plane)
• Chronometer
• Pen

Alternative forms of the PASS

Chien et al. (2007b) developed a short form PASS (SFPASS) by conducting an item analysis of the PASS in a sample of 278 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., and selecting items with the best measurement properties (i.e. highest internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. and greatest responsivenessThe ability of an instrument to detect clinically important change over time.
). The SFPASS focuses on assessment of bed mobility and sit-to-stand. The SFPASS comprises 5 items (Liaw et al., 2012):

• Standing on the nonparetic leg
• Supine to sitting up on the edge of the table
• Sitting on the edge of the table to supine
• Sitting to standing up
• Standing up to sitting down

SFPASS items are scored on a 3-point scale and total scores range from 0 to 15. The SFPASS is simpler and quicker to administer than the PASS (Liaw et al., 2012).

Persson et al. (2011) developed a Swedish version of the PASS (SwePASS) in response to perceived need to clarify scoring criteria and item descriptions. The SwePASS defines the scoring criteria “much help” as “support from 2 persons”, and “little help” as “support from 1 person”. Items 4, 7 and 10 have been clarified or modified. The SwePASS comprises the same 12 items as the PASS, and the same ordinal scale scoring (0-3), with a maximum score of 36.

Client suitability

Can be used with:

• Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., regardless of postural competencies.

Should not be used in:

• None reported

In what languages is the measure available?

• French
• English
• Swedish

Summary

What does the tool measure?	Balance
What types of clients can the tool be used for?	Patients following strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., regardless of balance performance
Is this a screeningTesting for disease in people without symptoms. or assessment tool?	Assessment
Time to administer	10 minutes
Versions	wePASS (Swedish version) SFPASS (5-item, 3-scale short form) PASS-3P (12-item, 3-scale form)
Other Languages	French, Swedish
Measurement Properties
ReliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .	Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.: – Three studies have reported excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS. – One study reported excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of PASS trunk control items (PASS-TC). – One study reported adequate to excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the SFPASS. Test-retest: – Three studies reported adequate to excellent intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings. of individual PASS items and excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society). of PASS total scores. Further, one study reported small limits of agreement using Bland-Altman plots, indicating high stability with low natural variation. – One study reported excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society). of individual items and total score of the SFPASS. Intra-rater: One study reported adequate to excellent same-day intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings. of the SwePASS in patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Inter-rater: – Two studies reported adequate to excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of individual PASS items and excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the PASS total score. – One study reported excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the PASS-TC. – One study reported excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the SwePASS.
ValidityThe degree to which an assessment measures what it is supposed to measure.	Content: No studies have reported on the content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension. of the PASS. Criterion: Concurrent: Four studies examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.” of the PASS and reported excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.” with the Berg Balance Scale, FMA modified balance scale (FMA-B), Trunk Impairment Scale (TIS), SFPASS and PASS-3P. Predictive: – Six studies reported that the PASS shows adequate to excellent predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks. for function at 90 days post-stroke or on discharge from rehabilitation, but poor predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks. of function after 1 year. Two studies reported excellent predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks. of mobility at 180 days post-stroke or on discharge from rehabilitation. – One study reported that the PASS-TC shows excellent predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks. of ADL function at 6 months post-stroke and is a stronger predictor of function than the BI or Fugl-Meyer Assessment (FMA) motor test. – Two studies reported that the SFPASS shows adequate to excellent predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks. for function on discharge from rehabilitation or at 90 days post-stroke. Construct: Convergent/Discriminant: – Four studies examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other. of the PASS and reported excellent correlations with the BI; FIM total score, transfer tasks and locomotor tasks; and motricity scores of the upper and lower limb. Adequate negative correlations were found with the star cancellation test of spatial inattention; pressure sensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.” of the upper and lower limb; and measurement of postural stabilization and postural orientation with respect to gravity. The PASS demonstrated no significant correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation. with the Ashworth Scale. – One study reported that the PASS-TC demonstrates excellent convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other. with the BI and FMA-B. – Two studies have examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other. of the SFPASS or PASS-3P and reported that both measures show excellent correlations with the BI and FIM. Known Groups: No studies have reported on the known-groups validityThe degree to which an assessment measures what it is supposed to measure. of the PASS.
Floor/Ceiling Effects	Three studies have reported no floor or ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” of the PASS from acute to chronic stages of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. recovery. However, one study reported a poor floor effectThe floor effect is when data cannot take on a value lower than some particular number. Thus, it represents a subsample for whom clinical decline may not register as a change in score, even if there is worsening of function/behavior etc. because there are no items or scaling within the test that measure decline from the lowest possible score. See also “ceiling effect.” at 90 days post-stroke.
Does the tool detect change in patients?	– Six studies have examined responsivenessThe ability of an instrument to detect clinically important change over time. and found that the PASS is able to detect change in strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. The PASS demonstrates good responsivenessThe ability of an instrument to detect clinically important change over time. before 90 days post-stroke but low responsivenessThe ability of an instrument to detect clinically important change over time. at later stages of recovery. Further, the PASS is more responsive to detecting change in moderate to severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. than mild strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. – Three studies have examined responsivenessThe ability of an instrument to detect clinically important change over time. in the PASS-3P or SFPASS and reported that both measures are able to detect change in acute and subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. SensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.” & specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative). : No studies have reported on the sensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.” or the specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative). of the PASS.
Acceptability	The PASS was designed for patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., regardless of balance function.
Feasibility	The PASS is quick and simple test to administer, and requires minimal equipment and no specialized training.
How to obtain the tool?	The tool is available on line: http://www.brightonrehab.com/wp-content/uploads/2012/02/Postural-Assessment-Scale-for-Stroke-Patients-PASS.pdf

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the Postural Assessment Scale for StrokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. Patients (PASS). Eleven papers were reviewed.

Floor/Ceiling Effects

Benaim et al. (1999) examined the frequency distribution and density trace of PASS scores in 58 patients at 30 and 90 days post-stroke. While a uniform distribution was noted at 30 days post-stroke, there was a pronounced peak around the highest values at 90 days as 38% of patients had achieved the maximum score. Testing on 30 age-matched healthy subjects revealed that 90% of participants achieved the maximum score.

Mao et al. (2002) examined the floor and ceiling effectA ceiling effect occurs when test items aren't challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes - the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also "floor effect." of the PASS on a sample of patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. at 14, 30, 90 and 180 days post-stroke. Floor and ceiling effects were adequate at all time points (floor effectThe floor effect is when data cannot take on a value lower than some particular number. Thus, it represents a subsample for whom clinical decline may not register as a change in score, even if there is worsening of function/behavior etc. because there are no items or scaling within the test that measure decline from the lowest possible score. See also "ceiling effect."
range 2.2-3.8%; ceiling effectA ceiling effect occurs when test items aren't challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes - the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also "floor effect." range 3.3-17.5%).

Chien et al. (2007b) examined the floor and ceiling effects of the PASS among 287 patients at 14 days post-stroke, and a second cohort of 197 patients. The PASS demonstrated no significant floor effects (6.3%, 6.1% respectively) or ceiling effects (2.8%, 1.7% respectively) in either cohort.

Chien et al. (2007b) also examined the floor and ceiling effects of the 5-item SFPASS among 287 patients at 14 days post-stroke, and a second cohort of 197 patients. The SFPASS demonstrated no significant ceiling effect in either cohort (7.0%, 8.4%). A poor floor effectThe floor effect is when data cannot take on a value lower than some particular number. Thus, it represents a subsample for whom clinical decline may not register as a change in score, even if there is worsening of function/behavior etc. because there are no items or scaling within the test that measure decline from the lowest possible score. See also "ceiling effect."
(20.2%) was seen in the first cohort, but was not evident in the second cohort (16.2%).

Yu et al. (2012) reported no significant floor or ceiling effectA ceiling effect occurs when test items aren't challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes - the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also "floor effect." of the PASS among 85 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. (most with acute strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. and severe disability) on admission to (<15%) or discharge from (<10%) a rehabilitation ward.

Reliability

Internal constancy:
Benaim et al. (1999) reported excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS (α=0.95) when examined on a sample of 58 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. using Cronbach α-coefficient. The authors concluded that the PASS is homogenous and is likely to produce consistent responses. Further, there was a strong correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the sums of maintaining-position and changing-position items (r=0.86, p<0.001).

Mao et al. (2002) examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS on a sample of 112 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. at 14, 30, 90 and 180 days post-stroke, using Cronbach’s α coefficient. Excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. was reported at all time points (α range = 0.94-0.96).

Hsieh et al. (2002) examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 182 patients with acute strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. Results from two raters indicated excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS-TC (α=0.93-0.94), measured using Cronbach’s α.

Chien et al. (2007b) examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS on a sample of 287 patients at 14 days post-stroke, and a second cohort of 197 patients. Excellent internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. (α=0.96) was reported in both cohorts, measured using Cronbach’s α.

Chien et al. (2007b) also examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the SFPASS on a sample of 287 patients at 14 days post-stroke, and a second cohort of 197 patients. Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. was adequate in the first cohort (α=0.66) and excellent in the second cohort (α=0.93), as measured using Cronbach’s α.

Chien et al. (2007b) noted that the high internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the PASS may indicate redundancy among items.

Test-retest:
Benaim et al. (1999) measured test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the PASS on 12 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., using α-coefficient for individual items and Pearson product moment correlationThe most commonly used method of computing a correlation coefficient between variables that are linearly related. Pearson’s r is a measure of association which varies from -1 to +1, with 0 indicating no relationship (random pairing of values) and 1 indicating perfect relationship
for the total score. The authors reported adequate to excellent reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
for individual items (average α=0.72, range 0.45 – 1) and excellent reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
for the total score (r=0.98, p<0.001). Further, a Bland-Altman plot showed that differences between scorings were weak (0.5) and homegenous (differences were within or very near the 95% confidence limits of the mean).

Chien et al. (2007a) examined the 2-week test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the PASS among 20 patients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., and reported excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
(ICC=0.84), measured using a 1-way random effects model intraclass correlation coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance..

Liaw et al. (2008) examined 7-day test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the PASS in a sample of 52 patients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., using the intraclass coefficient for relative reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
(i.e. the degree to which individuals maintain their position in a sample with repeated measures), and Bland-Altman plots and standard error of measurement (SEM) for absolute reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
(i.e. the degree to which repeated measurements vary for individuals). Relative test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
was excellent (ICC=0.97). Bland-Altman plots revealed small limits of agreement (-2.72 to 3.52), indicating high stability with low natural variation. The SEM was small (1.14%), indicating that the PASS is useful to identify real change.

Liaw et al. (2012) examined the 7-day test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
of the SFPASS among a sample of 52 patients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., using the weighted α statistic for individual items and intraclass correlation coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance. for the total score. The authors reported adequate to excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
for individual items (mean α=0.78, range 0.66 – 0.84) and excellent reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
for total scores (ICC=0.93, 95% CI 0.88-0.96). Bland-Altman plots of the differences between measurements from the two test sessions against the mean of the two test sessions for each patient revealed small limits of agreement (1.99 to -2.33), indicating high stability with low natural variation. Standard error of measurement (SEM) was 5.2%, representing a small and acceptable level of measurement error.
Note: When performing a Bland and Altman analysis, a mean difference close to zero indicates higher agreement between measurements.

Intra-rater:
Persson et al. (2011) examined the same-day intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the SwePASS in a sample of 114 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. The inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of items was excellent (r=0.88-0.98) when measured using Spearman’s rank correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
, and adequate to excellent (α=0.70-0.93) when measured using Kappa coefficient.

Inter-rater:
Benaim et al. (1999) measured inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the PASS using α-coefficient for individual item reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
and Pearson product moment correlationThe most commonly used method of computing a correlation coefficient between variables that are linearly related. Pearson's r is a measure of association which varies from -1 to +1, with 0 indicating no relationship (random pairing of values) and 1 indicating perfect relationship
for total score reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
. Two clinicians assessed patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. on the same day, with a total sample of 12 patients. The authors reported adequate to excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for individual items (average α=0.88, range 0.64-1) and excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the total score (r=0.99, p<0.001). Further, a Bland and Altman plot for inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
showed that differences between scorings were weak (0.5) and homegenous (differences were within or very near the 95% confidence limits of the mean).

Mao et al. (2002) examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the PASS using α-coefficient for individual item reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
and Pearson product moment correlationThe most commonly used method of computing a correlation coefficient between variables that are linearly related. Pearson's r is a measure of association which varies from -1 to +1, with 0 indicating no relationship (random pairing of values) and 1 indicating perfect relationship
for total score reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
. Two clinicians assessed patients at 14 days post-stroke on the same day, with a total sample of 112 patients. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for individual items was adequate to excellent (median α=0.88, range 0.61-0.96) and inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the total score was excellent (ICC=0.97, 95% CI 0.95-0.98).

Hsieh et al. (2002) examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 182 patients with acute strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. Results indicated excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the PASS-TC (ICC=0.97), measured using intraclass correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient.

Persson et al. (2011) examined the same-day inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the SwePASS in a sample of 114 patients with acute strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain., using Spearman’s rank correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
. The inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of items was excellent (r=0.77-0.99).

Validity

Content:

No studies have reported on the content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
of the PASS.

Criterion:

Concurrent :
Mao et al. (2002) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the PASS, Berg Balance Scale (BBS) and the Fugl-Meyer Assessment modified balance scale (FMA-B), using Spearman’s α correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient. A sample of 123 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. was followed at 14, 30 (n=110), 90 (n=93), and 180 (n=80) days after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. onset. There was excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
between the PASS and the FMA-B (α=0.95-0.97) and between the PASS and the BBS (α= 0.92-0.95) at all time points.

Wang et al. (2004) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the PASS, Berg Balance Scale (BBS) and modified versions of both assessments that used 3-level scales (12-item PASS-3P, 14-item BBS-3P) in a sample of 77 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., using Spearman’s α correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient and Intraclass CorrelationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
Coefficient. There was excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
between all measures (rho α 0.91, P<0.0001); of note, agreement between the PASS and the BBS (α=0.94, P<0.0001), and between the PASS and the PASS-3P (α=0.94, P<0.0001; ICC=0.97, 95% CI 0.96-0.98.) was excellent.

Chien et al. (2007b) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the PASS and the 5-item SFPASS in a sample of 287 patients at 14 days post-stroke, using a random effects model intraclass correlation coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance.. There was excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
between the PASS and the 5-item SFPASS (ICC= 0.98; 96% variance). This result was repeated in a subsequent cohort of 179 patients (ICC=0.98). Further, Bland-Altman plots revealed no systematic trend between the difference and mean score of the PASS and the 5-item SFPASS (mean difference 1.6, limits of agreement range from -3.7 to 6.8). This suggests that the PASS and the SFPASS can be used interchangeably.

Di Monaco et al. (2010) reported excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
between the PASS and the Trunk Impairment Scale (TIS) (α=0.849, P<0.001), measured in a sample of 60 patients on admission to inpatient rehabilitation.

Predictive:
Benaim et al. (1999) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS by comparing PASS scores at 30 days post-stroke with FIM scores at 90 days post-stroke on a sample of 58 patients. Correlations between the PASS and FIM total score (r=0.75, p<0.001), transfer items (r=0.74, p<0.006) and locomotion items (r=0.71, p<0.001) indicate that it is possible to predict functional recovery from PASS scores at 30 days post-stroke.

Mao et al. (2002) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS, Berg Balance Scale and the Fugl-Meyer Assessment modified balance scale at 14, 30 and 90 days post-stroke by comparison with the Motor Assessment Scale walking subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
score at 180 days post-stroke, in a sample of 123 patients. The PASS demonstrated excellent predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
at all time points (α=0.86-0.90), as measured using Spearman’s p correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient.

Hsieh et al. (2002) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) in a sample of 169 patients by comparing PASS-TC scores taken at 14 days post-stroke with Barthel Index (BI) and Frenchay ActivitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
Index (FAI) scores taken at 6 months post-stroke. The PASS-TC demonstrated excellent predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
(r=0.68, p<0.001), as measured using Pearson correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient. The PASS-TC was found to be a stronger predictor of comprehensive ADL function than the Barthel Index or the Fugl-Meyer motor test.

Wang et al. (2004) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS and a modified version of the PASS that used a 3-level scale (12-item PASS-3P) in patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. by comparing scores taken at 14 (n=226) and 30 days (n=202) post-stroke with Barthel Index (BI) scores taken at 90 days post-stroke, using Spearman’s α correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient. Both versions of the PASS demonstrated excellent predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
at 14 days (p=0.78) and 30 days (p=0.82) post-stroke.

Chien et al. (2007a) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS in a sample of 32 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. by comparing PASS score taken within 3 months of the strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. with Barthel Index and Frenchay ActivitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
Index scores taken approximately 1 year later. Results indicated poor predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
(r2=0.24), as measured using Pearson correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient.

Chien et al. (2007b) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS and SFPASS in a sample of 218 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. by comparing scores on each test at 14 days post-stroke with Barthel Index (BI) scores at 90 days post-stroke. Results indicated adequate predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS (r=0.49) and the SFPASS (r=0.48). The authors replicated the process on a second cohort of 179 patients by comparing PASS and SFPASS scores on admission to rehabilitation with BI scores on discharge from hospital. Results revealed excellent predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS (r=0.83) and the SFPASS (r=0.82), as measured using product-moment correlations.

Di Monaco et al. (2010) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS and the Trunk Impairment Scale (TIS) by comparing scores on admission to inpatient rehabilitation with FIM discharge scores, in a sample of 60 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. Results indicated excellent predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS (α=0.687, p<0.001), as measured using Spearman rank correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
. PASS admission scores were also significantly associated with FIM change scores (P<0.001), FIM effectiveness (P=0.017) and destination at discharge (P=0.032).

Yu et al. (2012) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS and the Balance Computerized Adaptive Test (Balance CAT) by comparing scores on admission to a rehabilitation ward with Barthel Index (BI) and StrokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. Rehabilitation Assessment of Movement mobility subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
(MO-STREAM) discharge scores in a sample of 85 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. Correlations between PASS and BI scores (α =0.62, r2=0.39, p<0.001) and between PASS and MO-STREAM scores (α =0.80, r2=0.63, p<0.001) indicated sufficient predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the PASS, as measured using α and r2 from a simple linear regression analysis. This indicates that PASS scores at admission can predict discharge function and mobility.

Construct:

Convergent/Discriminant :
Benaim et al. (1999) examined correlations between PASS performance and clinical scales of functional status, motricity, spasticityInvoluntary muscle tightness and stiffness that can occur after a stroke. It is characterized by exaggerated deep tendon reflexes that interfere with muscular activity, gait, movement, or speech. Spasticity can increase initially but wane down later on, after stroke.
, spatial inattention and somatosensory threshold among 58 patients at 30 days post-stroke, using Pearson correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficients. Excellent correlations were found with FIM total score (r=0.73), transfer tasks (r=0.82) and locomotor tasks (r=0.73); and motricity scores of the lower limb (r=0.78) and upper limb (r=0.63). Adequate negative correlations were found with the star cancellation test of spatial inattention (r=-0.53) and pressure sensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.”
of the lower limb (r=-0.45) and upper limb (r=-0.42). There was no significant correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
with spasticityInvoluntary muscle tightness and stiffness that can occur after a stroke. It is characterized by exaggerated deep tendon reflexes that interfere with muscular activity, gait, movement, or speech. Spasticity can increase initially but wane down later on, after stroke.
, measured using the Ashworth Scale. The authors also examined the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between PASS performance and equilibrium, measured using a rocking platform, among a smaller sample of 31 patients at 90 days post-stroke, and reported adequate negative correlations with measurement of postural stabilization (r=-0.48) and postural orientation with respect to gravity (r=0.36).

Mao et al. (2002) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the PASS, Berg Balance Scale and the Fugl-Meyer Assessment modified balance scale by comparison with the Barthel Index (BI), using Spearman’s p correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient. A sample of 123 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. was followed at 14, 30 (n=110), 90 (n=93), and 180 (n=80) days after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. onset. There was excellent convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
between the PASS and the BI (α=0.88-0.92) at all time points.

Hsieh et al. (2002) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the trunk control items of the PASS (PASS-TC: items 1, 6, 7, 8, 9) by comparison with the Barthel Index (BI) and Fugl-Meyer balance test (FM-B), in a sample of 182 patients at 14 days post-stroke. The PASS-TC demonstrated excellent convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
with the BI (r=0.89) and the FM-B (r=0.73), using Pearson correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient.

Wang et al. (2004) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the PASS and the PASS-3P by comparison with the Barthel Index (BI), in a sample of 77 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. The PASS and the PASS-3P both demonstrated excellent convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
with the BI (α=0.84, (α=0.82 respectively), measured using Spearman p correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient.

Chien et al. (2007b) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the PASS and the 5-item SFPASS by comparison with the Barthel Index (BI) and FIM in a sample of 287 patients at 14 days post-stroke. The PASS and the SFPASS both demonstrated excellent correlations with the BI (PASS r=0.87; SFPASS r=0.86) and the FIM (PASS r=0.75; SFPASS r=0.75).

Known Group:
No studies have reported on the known-groups validityThe degree to which an assessment measures what it is supposed to measure.
of the PASS.

Responsiveness

Mao et al. (2002) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS in a sample of 123 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. by comparing scores taken at 14, 30 (n=110), 90 (n=93) and 180 (n=80) days post-stroke. There was a significant change in PASS scores at all stages (14-30 days, 30-90 days, 90-180 days, 14-90 days and 14-180 days post-stroke), measured using Wilcoxon matched-pairs signed-rank tests. Effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
was large at the interval between 14-30 days post-stroke (ES=0.89), became moderate in the interval between 30-90 days (ES=0.64) and low in the interval 90-180 days (ES=0.31). The overall effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
(14-180 days) was large (ES=1.12). These results indicate that the PASS demonstrates good responsivenessThe ability of an instrument to detect clinically important change over time.
before 90 days post-stroke but low responsivenessThe ability of an instrument to detect clinically important change over time.
at later stages of recovery. The authors also examined responsivenessThe ability of an instrument to detect clinically important change over time.
according to strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. severity and found that the PASS is more responsive to detecting change in moderate to severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. than mild strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. across most time intervals. The overall effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
(14-180 days) was largest among patients with severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (ES=1.54).

Wang et al. (2004) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS and the PASS-3P in patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. by comparing scores taken at 14 days (n=202), 30 days (n=167) and 90 days (n=167) post-stroke. There was a significant change in PASS and PASS-3P scores at all stages (14-30 days, 30-90 days and 14-90 days post-stroke), measured using Wilcoxon matched-pairs signed-rank tests. Both measures demonstrated a large effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
in the interval 14-30 days post-stroke (SRM=0.84 and 0.86 respectively) and 14-90 days post-stroke (SRM=1.02 and 1.04 respectively), but only a moderate effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
in the interval 30-90 days post-stroke (SRM=0.65 and 0.67 respectively), measured using standardized response meanThe standardized response mean (SRM) is calculated by dividing the mean change by the standard deviation of the change scores.
(SRM). The authors examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS and the PASS-3P according to severity of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. – mild (Fugl-Meyer Assessment score ≥ 80), moderate (FMA score 36-79) and severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (FMA score 0-35). Both measures showed a moderate effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
among patients with mild strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (PASS SRM range 0.43-0.78; PASS-3P SRM range 0.46-0.78), moderate to large effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
among patients with moderate strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (PASS SRM range 0.52-1.12; PASS-3P SRM range 0.56-1.19), and a large effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
among patients with severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (PASS SRM range 0.92-1.35; PASS-3P SRM range 0.92-1.34). The effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
of both measures was consistently larger in the intervals 14-30 days post-stroke and 14-90 days post-stroke, than 30-90 days post-stroke.

Chien et al. (2007a) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS in a sample of 40 patients with subacute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., measured using Cohen’s effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
. The PASS was administered twice over a 2-week interval, during which time patients received an intensive rehabilitation program that comprised postural training and weight shift exercises for more than 2 hours per day, 5 days a week. The effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
after 2 weeks was small (d=0.41). The minimal detectable change (MDC)Minimal Detectable Change (MDC) refers to the minimal amount of change outside of error that reflects true change by a patient between two time points (rather than a variation in measurement). (i.e. the threshold value that determines whether score changes are beyond chance) was 2.22 (95% CI) at an individual score level, and 0.50 (95% CI) at a group score level.

Chien et al. (2007b) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS in a sample of 262 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. The change score from 14 days post-stroke to 30 days post-stroke was significant (4.9, p<0.01) and the effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
was small (ES=0.42). A small effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
(ES=0.43) was also seen in a subsequent cohort of 179 patients who were assessed at admission to rehabilitation and again on discharge from hospital.

Chien et al. (2007b) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the 5-item SFPASS in a sample of 262 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. The change score from 14 to 30 days post-stroke was significant (5.4, p<0.01) and the effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
was small (ES=0.44). A small effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
(ES=0.42) was also seen in a subsequent cohort of 179 patients who were assessed at admission to rehabilitation and again on discharge from hospital.

Chien et al. (2007b) reported on the Standard Error of Measurement (i.e. an estimate of the dispersion of scores that would be obtained if the measure was administered to a patient multiple times) of the PASS and the 5-item SFPASS in a cohort of 287 patients at 14 days post-stroke. The SEM of the PASS was 2.4 (4.7, 95% CI). The SEM of the 5-item SFPASS in the same cohort was 3.4 (6.7, 95% CI). This score is lower than 10% of the highest possible score of 36, which indicates that the measurement error does not exceed clinical importance.

Liaw et al. (2008) examined the smallest real difference (SRD – the smallest change threshold that indicates a real improvement for a single individual) of the PASS in a sample of 52 patients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Participants were assessed by the same clinician on 2 occasions, 7-days apart. The SRD was 3.2, indicating that a change of more than 4 points in the total score for the PASS in chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. patients is not likely to be attributable to chance variation or measurement error.

Liaw et al. (2012) examined the minimal detectable change (MDC)Minimal Detectable Change (MDC) refers to the minimal amount of change outside of error that reflects true change by a patient between two time points (rather than a variation in measurement). of the Short Form PASS (SFPASS) in a sample of 52 patients with chronic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Participants were assessed by the same clinician on two occasions, 7 days apart. Results indicate that a change in an individual’s SFPASS scores greater than 2.16 points can be interpreted as true change (95% CI).

Yu et al. (2012) examined the internal and external responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS in a sample of 85 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. There was a significant change in PASS scores from admission to discharge (Wilcoxon Z=7.7, p<0.001), and the effect sizeEffect size (ES) is a name given to a family of indices that measure the magnitude of a treatment effect. Unlike significance tests, these indices are independent of sample size. The ES is generally measured in two ways: as the standardized difference between two means, or as the correlation between the independent variable classification and the individual scores on the dependent variable. This correlation is called the “effect size correlation”.
was large (d=0.87), indicating adequate internal responsivenessThe ability of an instrument to detect clinically important change over time.
. External responsivenessThe ability of an instrument to detect clinically important change over time.
was calculated by comparing PASS change scores (admission to discharge) with change scores from the Barthel Index (BI) and the mobility subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
of the StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. Rehabilitation Assessment of Movement (MO-STREAM), using α and r2 from a simple linear regression analysis. Results revealed a fair association between PASS and BI changes scores (α =0.44, r2=0.20, p<0.001) and a moderate association between PASS and MO-STREAM change scores ((α =0.77, r2=0.59, p<0.001) indicating sufficient external responsivenessThe ability of an instrument to detect clinically important change over time.
of the PASS to changes in function and mobility following strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..

SensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.”
 & specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative).
:
No studies have reported on the sensitivitySensitivity refers to the probability that a diagnostic technique will detect a particular disease or condition when it does indeed exist in a patient (National Multiple Sclerosis Society). See also “Specificity.”
 or the specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative).
 of the PASS.

References

• Barros de Oliveira, C., Torres de Medeiros, I.R., Ferreira Frota, N.A., Greters, M.E., & Conforto, A.B. (2008). Balance control in hemiparetic stroke patients: main tools for evaluation. Journal of Rehabilitation Research and Development, 45(8), 1215-26.
• Benaim, C., Perennou, D.A., Villy, J., Rousseaux, M., & Pelissier, J.Y. (1999). Validation of a standardized assessment of postural control in stroke patients: The Postural Assessment Scale for Stroke Patients (PASS). Stroke, 30, 1862-8.
• Blum, L. & Korner-Bitensky, N. (2008). Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Physical Therapy, 88, 559-66.
• Chien, C-W., Hu, M-H., Tan, P-F., Sheu, C-F., & Hsieh, C-L. (2007a). A comparison of psychometric properties of the Smart Balance Master system and the Postural Assessment Scale for Stroke in people who have had mild stroke. Archives of Physical Medicine and Rehabilitation, 88, 374-80.
• Chien, C-W., Lin, J-H., Wan, C-H., Hsueh, I-P., Sheu, C-F., & Hsieh, C-L. (2007b). Developing a short form of the Postural Assessment Scale for People with Stroke. Nuerorehabilitation and Neural Repair, 21, 81-90.
• Di Monaco, M., Trucco, M., Di Monaco, R., Tappero, R., & Cavanna, A. (2010). The relationship between initial trunk control or postural balance and inpatient rehabilitation outcome after stroke: a prospective comparative study. Clinical Rehabiltiation, 24, 543-54.
• Hseih, C-L., Sheu, C-F., Hsueh, I-P., & Wang, C-H. (2002). Trunk control as an early predictor of comprehensive activities of daily living function in stroke patients. Stroke, 33, 2626-30.
• Liaw, L-J., Hsieh, C-L., Hsu, M-J., Chen, H-M., Lin, J-H., & Lo, S-K. (2012). Test-retest reproducibility of two short-form balance measures used in individuals with stroke. International Journal of Rehabilitation Research, in press. Epub ahead of print retrieved from http://journals.lww.com/intjrehabilres/Abstract/publishahead/Test_retest_reproducibility_of_two_short_form.99818.aspx
• Liaw, L-J., Hsieh, C-L., Lo, S-K., Chen, H-M., Lee, S., & Lin, J-H. (2008). The relative and absolute reliability of two balance performance measures in chronic stroke patients. Disability and Rehabilitation, 30(9), 656-61.
• Mao, H-F., Hsueh, I-P., Tang, P-F., Sheu, C-F., & Hsieh, C-L. (2002). Analysis and comparison of the psychometric properties of three balance measures for stroke patients. Stroke, 33, 1022-7.
• Persson, C.U., Hansson, P-O., Danielsson, A., & Sunnerhagen, K.S. (2011). A validation study using a modified version of Postural Assessment Scale for Stroke Patients: Postural stroke study in Gothenburg (POSTGOT). Journal of NeuroEngineering and Rehabilitation, 8, 57-64.
• Wang, C.H., Hsueh, I.P., Sheu, C.F., Yao, G., & Hsieh, C.L. (2004). Psychometric properties of 2 simplified 3-level balance scales used for patients with stroke. Physical Therapy, 84(5), 430-8.
• Yu, W-H., Hsueh, I-P., Hou, W-H., Wang, Y-H., & Hsieh, C-L. (2012). A comparison of responsiveness and predictive validity of two balance measures in patients with stroke. Journal of Rehabilitation Medicine, 44, 176-80.

See the measure

How to obtain the PASS?

The PASS is available on line at: http://www.brightonrehab.com/wp-content/uploads/2012/02/Postural-Assessment-Scale-for-Stroke-Patients-PASS.pdf