Motor Activity Log (MAL)

Purpose

The Motor Activity Log (MAL) is a subjective measure of an individual’s real life functional upper limb performance. The MAL is administered by semi-structured interview to determine (a) how much, and (b) how well the individual uses his upper limb in his own home (Ashford et al., 2008, Li et al., 2012; Simpson & Eng, 2013).

In-Depth Review

Purpose of the measure

The Motor Activity Log (MAL) was developed by Taub et al. (1993) as a subjective outcome measure of an individual’s real life functional upper limb performance. The MAL is administered by semi-structured interview to determine (a) how much (Amount of Use – AOU), and (b) how well the individual uses his upper limb (Quality of Movement – QOM) in his own home (Ashford et al., 2008, Li et al., 2012; Simpson & Eng, 2013).

Available versions

There are four versions of the original MAL-30, according to number of items.

• MAL-14: Contains unilateral and simple items, to detect change in individuals with limited arm function.
• MAL-26: Contains the same items as the MAL-14 as well as 11 additional items and 1 optional item chosen by the patient; this version includes some bilateral tasks.
• MAL-28: Contains the same items as the MAL-14 and MAL-26, and additional items that challenge reach and strength.
• MAL-12: A short version of the MAL-28 (Ashford et al., 2008).

Other adaptations of the MAL include:

• Graded Motor Activity Log (Morera Silva et al., 2018)
• Lower-Functioning Motor Activity Log (LF-MAL)
• Lower-Extremity Motor Activity Log
• Pediatric Motor Activity Log – Revised

Features of the measure

The MAL is comprised of two scales:

• Amount of Use (AOU) scale – the amount the individual uses the paretic arm; and
• Quality of Movement (QOM) scale – the patient’s perceived quality of movement while performing the functional activity (Ashford et al., 2008).

The MAL-QOM scale captures components of amount of arm use and has been shown to be more reliable than the MAL-AOU scale, and as such can be used independently (Uswatte & Taub, 2005).

Items:

Items the original MAL-30

1. Turn on a light with a light switch
2. Open drawer
3. Remove an item from a drawer
4. Pick up phone
5. Wipe off a kitchen counter or other surface
6. Get out of a car
7. Open refrigerator
8. Open a door by turning a door knob/handle
9. Use a TV remote control
10. Wash your hands
11. Turning water on/off with knob/lever on faucet
12. Dry your hands
13. Put on your socks
14. Take off your socks
15. Put on your shoes
16. Take off your shoes
17. Get up from a chair with armrests
18. Pull chair away from table before sitting down
19. Pull chair toward table after sitting down
20. Pick up a glass, bottle, drinking cup, or can
21. Brush your teeth
22. Put on makeup base, lotion, or shaving cream on face
23. Use a key to unlock a door
24. Write on paper
25. Carry an object in your hand
26. Use a fork or a spoon for eating
27. Comb your hair
28. Pick up a cup by a handle
29. Button a shirt
30. Eat half a sandwich or finger foods

Additional Items for the MAL-45

• Removing bills from a wallet
• Taking individual coins out of a pocket or purse
• Removing keys out of a pocket or purse
• Using a zipper pull
• Pouring liquid from a bottle
• Buckling a belt
• Popping top of beverage can
• Removing top from a medicine bottle
• Keypad press
• Use of keyboard/computer
• Putting on or taking off watch band
• Putting on glasses
• Pumping a soap dispenser
• Swiping a credit card or a card for an ATM
• Adjusting a home or hotel air conditioner or heat

Items of the MAL-12:

1. Pick up phone
2. Open a door by turning a door knob
3. Eat half a sandwich or finger food
4. Turn water on/off with faucet
5. Pick up a glass
6. Pick up toothbrush and brush teeth
7. Use a key to open a door
8. Letter writing/typing
9. Use removeable computer storage
10. Pick up fork or spoon, use for eating
11. Pick up cup by handle
12. Carry an object from place to place

Items of the MAL-14:

1. Putting arm through coat sleeve
2. Steady myself while standing
3. Carry an object from place to place
4. Pick up fork or spoon, use for eating
5. Comb hair
6. Pick up cup by handle
7. Hand craft/card playing
8. Hold a book for reading
9. Use towel to dry face or other body part
10. Pick up a glass
11. Pick up toothbrush and brush teeth
12. Shaving/makeup
13. Use a key to open a door
14. Letter writing/typing

The MAL-26 includes the 14 items from the MAL-14 as well as the following items:

15. Pour coffee/tea
16. Peel fruit/potatoes
17. Dial number on the phone
18. Open/close a window
19. Open an envelope
20. Take money out of a wallet or purse
21. Undo buttons on clothing
22. Buttons on clothing
23. Undo a zip
24. Do up a zip
25. Cut fingernails (affected hand)
26. Other optional activity

Items of the MAL-28:

1. Turn on a light with a light switch
2. Open a drawer
3. Remove item of clothing from drawer
4. Pick up phone
5. Wipe kitchen counter
6. Get out of car
7. Open refrigerator
8. Open a door by turning a door knob
9. Use a TV remote control
10. Wash your hands
11. Turn water on/off with faucet
12. Dry your hands
13. Put on your socks
14. Take off your socks
15. Put on your shoes
16. Take off your shoes
17. Get up from chair with armrests
18. Pull chair away from table before sitting
19. Pull chair toward table after sitting
20. Pick up a glass
21. Pick up toothbrush and brush teeth
22. Use a key to unlock a door
23. Steady self while standing
24. Carry an object from place to place
25. Comb hair
26. Pick up cup by handle
27. Buttons on clothing (shirt, trousers)
28. Eat half a sandwich or finger food

For each item, the individual is asked whether he/she attempted the activity in the past 7 days, and the relevant score is assigned according to his/her response. The examiner can verify the response by paraphrasing it back to the individual (Uswatte & Taub, 2005). The MAL can also be used with caregivers.

Scoring:

The MAL is administered by semi-structured interview and items are scored by patients according to their performance of each task over the past 7 days; the MAL-28 can also be used to score performance over the past 3 days (Ashford et al., 2008; Uswatte & Taub, 2005).

The MAL adopts a 6-point ordinal scale, although patients can attribute a half-score, resulting in 11-point Likert scales with specified anchoring definitions at 6 points (Uswatte & Taub, 2005):

Amount of Use scale scoring:

• 0: Never – The weaker arm was not used at all for that activity.
• 1: Very rarely – Occasionally used the weaker arm, but only very rarely.
• 2: Rarely – Sometimes used the weaker arm but did the activity most of the time with the stronger arm.
• 3: Half pre-stroke – Used the weaker arm about half as much as before 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..
• 4: Three quarters pre-stroke – Used the weaker arm almost as much as before 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..
• 5: Same – Used the weaker arm as often as before 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..

Quality of Movement scale scoring:

• 0: Never – The weaker arm was not used at all for that activity.
• 1: Very rarely – The weaker arm was moved during the activity but was not very helpful.
• 2: Rarely – The weaker arm was of some use during the activity but needed some help from the stronger arm but moved very slowly or with difficulty.
• 3: Fair – The weaker arm was used for that activity, but the movements were slow or were made only with some effort.
• 4: Almost normal – The movements made by the weaker arm for the activity were almost normal but not quite as fast or accurate as normal
• 5: Normal – The ability to use the weaker arm for that activity was as good as before 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..

Scale total scores (summary scores) are the mean of the item scores.

What to consider before beginning:

The MAL is subject to experimenter bias and also the patient’s ability to accurately recall upper limb use (Page & Levine, 2003; Uswatte & Taub, 2005).

Ashford et al. (2008) noted an inadequate relationship between overall/item scores and the qualitative meaning, and an unclear Minimal clinically important difference.

Taub & Uswatte (2000) discuss the use of the MAL as an outcome measure in Constraint-Induced Movement Therapy (CIMT) research and recommend an upper cut-off score of 2.5 on the MAL-AOU, as the effect 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. can impose an upper physiological limit on the amount of improvement that can be produced. The authors also note that individuals who score > 2.5 do not demonstrate learned non-use, which is the aim of CIMT.

Time:

All versions of the MAL are administered through structured interview with the patient and/or carer and require more than 10 minutes to administer. (Ashford et al., 2008).

Training requirements:

The MAL can be administered by health professionals who have reviewed the manual and literature.

Equipment:

Survey instrument and pencil.

Client suitability

Can be used with:

• The MAL is suitable for use with adults and elderly adults 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. and their caregivers. It is suitable for use in the subacute and 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.

Should not be used in:

Not specified.

• The MAL is often used to measure outcomes following constraint induced movement therapy (Li et al., 2012; Page, 2003). The MAL is commonly used in research in conjunction wi with the Wolf Motor Function Test, Fugl-Meyer Assessment or the Action Research Arm Test (Santisteban et al., 2016; Simpson & Eng, 2013).

In what languages is the measure available?

• Brazilian-Portuguese (Saliba et al., 2011)
• English
• German (Khan et al., 2013)
• Portuguese (Pereira et al., 2011)
• Turkish translation and cultural adaptation (Cakar et al., 2010).

Summary

What does the tool measure?	Real life upper limb performance.
What types of clients can the tool be used for?	Individuals 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. and their caregivers.
Is this a screeningTesting for disease in people without symptoms. or assessment tool?	Assessment
What domain of the ICF does this measure?	Activity/participation
Time to administer	20 minutes
Versions	MAL-30 MAL-28 MAL-26 MAL-14 MAL-12 Graded Motor Activity Log Lower-Functioning Motor Activity Log (LF-MAL) Lower-Extremity Motor Activity Log Pediatric Motor Activity Log – Revised
Other Languages	Brazilian-Portuguese, English, German, Portuguese, Turkish.
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.: – MAL-14: Two studies 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.. – MAL: 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.; 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. among patients with mild-moderate hemiparesis and 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. among patients with severe hemiparesis. – MAL-28 (Turkish): 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.. – MAL-30 (German): 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.. – Grade 4/5 MAL: 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.. Test-retest: – MAL-14: 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). ; one study 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). . – MAL: 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). ; one study 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). . – MAL-28 (Turkish): 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). . – MAL-28 (Brazilian): 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). . – MAL-45: 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). . – Grade 4/5 MAL: 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). . Intra-rater: No studies have reported on the 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 MAL. Inter-rater: MAL-14: One study reported adequate 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. .
ValidityThe degree to which an assessment measures what it is supposed to measure.	Content: No studies have reported on 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 MAL. Criterion: Concurrent: – MAL-14: One study reported excellent correlations with accelerometry. – MAL: Three studies reported an excellent 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 SIS – Hand function domain; adequate correlations with the BBT, ARAT, FAI; poor to adequate correlations with SIS, SS-QOL, NEADL; and poor correlations with the Nine Hole Peg Test. – MAL-30 (German): One study reported excellent negative correlations with WMFT-PT; excellent correlations with WMFT-FA and Grip strength scores, CMSA – Arm and Hand scores, isometric strength. – MAL-45: 1 study reported excellent correlations with the Abilhand. Predictive: No studies have reported on 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 MAL. Construct: – MAL-14: One study reported excellent correlations between QOM and AOU patient/carer change scores; one study reported an excellent 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 AOU and QOM scales. – MAL: One study reported an excellent 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 AOU and QOM scales; one study reported an adequate 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 AOU and QOM scales; one study conducted item analysis and removed two items due to low item-total correlations and 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 . coefficients; one study conducted item fit analysis and principal component analysis. – MAL (Brazilian): One study reported an excellent 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 AOU and QOM scales. – MAL-30 (German): One study reported excellent correlations between AOU and QOM scales. – MAL-28 (Turkish): One study reported an excellent 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 AOU and QOM scales. – LF-MAL: One study reported an adequate 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 AOU and QOM scales. Convergent/Discriminant: – MAL-14: Three studies reported excellent correlations with ARAT, accelerometry, Simple Test for Evaluating Hand Function (STEF). – MAL: Seven studies reported excellent correlations with Actual Amount of Use Test, WMFT; adequate to excellent correlations with accelerometry ratios, SIS 2.0 – Hand function scale, FMA-UE; adequate correlations with ARAT, Motor Assessment Scale – Upper Extremity, 16 Hole Peg Test, grip strength; SF-36 – Physical domain; poor to adequate correlations with accelerometry ratios of the less affected arm; poor correlations with the SIS 2.0 – Mobility scale. – MAL-28 (Turkish): One study reported excellent correlations with WMFT-FA; adequate negative correlations with the WMFT-PT. – MAL (Brazilian): One study reported adequate correlations with grip strength of the more affected arm. Known Group: MAL: One study reported correlations with accelerometry was stronger among patients with paresis of the dominant arm vs. the non-dominant arm.
Floor/Ceiling Effects	– Floor effects are evident when detecting change in lower level and passive functional tasks. – One study found modest floor effects when the MAL-28 was administered to patients with upper extremity motor recovery at Brunnstrom stage III and higher; and modest floor effects when the LF-MAL was administered to patients with upper extremity motor recovery at Brunnstrom stage III and lower.
Does the tool detect change in patients?	The MAL can be used to detect change
Acceptability	The MAL reflects real life functional performance. It is simple and non-invasive to administer.
Feasibility	The MAL is a free tool that requires no additional equipment. It can be administered in the clinical setting or the patient’s home. No additional training is required.
How to obtain the tool?	Click here to see the Motor Activity Log manual.

Psychometric Properties

Overview

A literature search was conducted to identify all relevant publications on the psychometric properties of the MAL. Twenty-six studies were identified, most of which included patients in the chronic phase 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. This review includes different versions of the MAL – the original MAL-30, MAL-28, MAL-14, MAL-45, LF-MAL, Grade 4/5 MAL and Turkish, Brazilian and German versions.

Floor/Ceiling Effects

Chuang et al. (2017) examined floor/ceiling effects of the 30-item MAL in a sample of 403 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.. The MAL was administered to patients with motor recovery of the proximal and distal upper limb at Brunnstrom stage III and higher. Results showed modest floor effects within this cohort, whereby 17.3% of participants received minimum scores on the MAL.

Chuang et al. (2017) examined floor/ceiling effects of the LF-MAL in a sample of 134 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.. The LF-MAL was administered to patients with motor recovery of the proximal and distal upper limb at Brunnstrom stage III and lower. Results showed modest floor effects within this cohort, whereby 16.4% of participants received minimum scores on the LF-MAL.

Reliability

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.:
van der Lee et al. (2004) examined 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 MAL-14 in a sample of 56 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 Cronbach’s alpha. 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.
among items was excellent for the MAL-AOU (a = 0.87) and the MAL-QOM (a = 0.90). Limits of agreement ranged from -0.70 to 0.85 for the MAL-AOU and from -0.61 to 0.71 for the MAL-QOM, indicating reproducibility sufficient to detect an individual change of approximately 12-15% of the range of the scale.

Uswatte et al. (2005b) examined 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 MAL-14 in a sample of 41 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 their caregivers, using Cronbach’s alpha. 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.
among items was excellent for patients’ MAL-QOM (a = 0.87) and caregivers’ MAL-AOU and MAL-QOM (a > 0.83). The authors also examined 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 MAL-14 (QOM scale only) in a sample of 27 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.. 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.
among items was excellent for the MAL-QOM (a = 0.81).

Uswatte et al. (2006b) examined 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 MAL-28 in a sample of 222 patients with subacute/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 their caregivers, using Cronbach’s alpha. Responses from both patient and caregiver groups showed excellent 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.
among items for the MAL-AOU (patients a = 0.94; caregivers a = 0.95) and the MAL-QOM (patients a = 0.94; caregivers a = 0.95).

Huseyinsinoglu et al. (2011) examined 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 MAL-28 (Turkish version) in a sample of 30 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’s alpha. 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 excellent for the MAL-AOU (a = 0.96) and MAL-QOM (a = 0.96).

Khan et al. (2013) examined 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 MAL-30 (German version) in a sample of 42 patients with acute to 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 Cronbach’s alpha. Measures were taken at baseline, discharge from rehabilitation and at 6-month follow-up. 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. for the MAL-AOU and MAL-QOM were excellent at all timepoints (a = 0.98-0.995). The authors also calculated 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. based on an elimination procedure of items that scored “N/A” down to 26 items and reported that 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. remained high at all timepoints (a = 0.94-0.98).

Taub et al. (2013) reported on 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 Grade 4/5 MAL, referencing unpublished data from Morris (2009) that used a sample of 30 individuals 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’s alpha. 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. for the Grade 4/5 MAL was excellent (a = 0.95).

Chuang et al. (2017) examined the 6-point rating system of the MAL and found rater difficulty discriminating among the 6 levels of functional ability. Results showed that 15 items of the MAL-AOU and MAL-QOM displayed disordering of step difficulty. Accordingly, the 6 levels were collapsed into 4 levels to restore reversed threshold (0 = 0; 1-2 = 1; 3-4 = 2; 5 = 3); using the 4-point system 9 items still showed disordered ordering, so the levels were further collapsed into 2 categories (0 = 0; 1 to 3 = 1), at which point all items exhibited ordering. The authors examined unidimensionality of the 30-item MAL in a sample of 403 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 revised scoring system. Item fit analysis of the MAL revealed that 7 items* of the MAL-AOU and MAL-QOM were a poor fit and were removed. Principal component analysis (PCA) of the remaining 23 items showed that Rasch measures accounted for 76% of the variance for both the MAL-AOU and MAL-QOM, with an eigenvalue of the first residual factor of 2.7. This indicates that the 23 items constitute unidimensional constructs. The authors examined 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 .
of the revised MAL (23 items, 4-point rating system), using Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. With Pearson separation values of 2.4 and 2.6 for the MAL-AOU and MAL-QOM respectively, the revised version was sensitive to distinguish among 3 strata of upper limb performance. Pearson 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 .
coefficients were 0.85 and 0.87 (respectively), suggesting good 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 .
. Results showed no Differential Item Functioning (DIF) items across age, gender or hand dominance. Item difficulty hierarchy was consistent with clinical expectation, however items were more difficult than individuals’ ability, suggesting unsuitable targeting for the participants of this sample.

* Misfit items: (6) Get out of car; (12) Dry your hands; (18) Pull a chair away from the table before sitting down; (19) Pull chair toward table after sitting down; (21) Brush your teeth; (24) Write on paper; (29) Button a shirt.

Chuang et al. (2017) examined the 6-point rating system of the LF-MAL and found disordered thresholds; accordingly, the 6 levels were collapsed into 3 levels to restore reversed threshold (0 = 0; 1-3 = 1; 4-5 = 2); this 3-point rating system achieved step ordering. The authors examined unidimensionality of the LF-MAL in a sample of 134 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 revised 3-point scoring system. Item fit analysis of the LF-MAL-AOU revealed that 6 items were out of the acceptable range; PCA of the remaining 24 items showed that the Rasch dimension explained 70.5% of the variance, with an eigenvalue of 2.6 of the first residual factor. Item fit analysis of the LF-MAL-QOM revealed that 7 items were out of the acceptable range; PCA of the remaining 23 items showed that the Rasch dimension explained 71.0% of the variance, with an eigenvalue of the first residual factor of 2.5. The authors examined 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 .
of the revised LF-MAL (25 items, 3-point rating system), using Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. With Pearson separation values of 1.9 for both the LF-MAL-AOU and LF-MAL-QOM, the revised version was sensitive to distinguish 2 strata of upper limb performance. Pearson 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 .
coefficients were 0.79 for both the LF-MAL-AOU and LF-MAL-QOM, indicating acceptable 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 .
. Results showed no DIF items across age, gender or hand dominance. Item difficulty hierarchy was consistent with clinical expectation, however items were more difficult than individuals’ ability, suggesting unsuitable targeting for the participants of this sample.

* Misfit items: (5) Wipe off a kitchen counter or another surface; (6) Get out of a car; (7) Open a refrigerator; (19) Apply soap to your body while bathing (LF-MAL-QOM only); (21) Brush your teeth; (23) Steady yourself while standing; (24) Carry an object in your hand.

Moreira Silva et al. (2018) examined 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 MAL-30 in a sample of 66 individuals 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 Cronbach’s alpha. Participants were classified according to upper extremity motor function using the Fugl-Meyer Assessment – Upper Extremity (FMA-UE): mild to moderate hemiparesis (FMA-UE ≥ 32, n = 49) or severe hemiparesis (FMA-UE ≤31, n = 17). 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 MAL-AOU and MAL-QOM was excellent among participants with mild-moderate hemiparesis (a = 0.95), and adequate to excellent among participants with severe hemiparesis (MAL-AOU: a = 0.79; MAL-QOM: a = 0.89). Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
was used to further evaluate 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 .
of the MAL-30. Item calibration of the MAL-AOU and MAL-QOM revealed one misfit (#19: Pull a chair toward table after sitting down). Item separation index of the MAL-AOU and MAL-QOM was 2.92 and 2.59 (respectively) suggesting 5 levels of difficulty for the MAL-AOU and 4 levels of difficulty for the MAL-QOM. Pearson separation index of the MAL-AOU and MAL-QOM was 2.62 and 2.58 (respectively), suggesting 4 ability levels for both the MAL-AOU and the MAL-QOM.

Test-retest:
Miltner et al. (1999) examined 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 MAL in a sample of 15 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.. Measures were taken within a 2-week interval before participants began constraint-induced movement therapy. 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 (r = 0.98).

Johnson et al. (2003) examined 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 MAL-45 in a sample of 12 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 Pearson’s 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. Measures were taken within a 3-week interval. 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 for the MAL-AOU (r=0.96) and MAL-QOM (r = 0.99).

van der Lee et al. (2004) examined 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 MAL-14 in a sample of 56 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 Bland and Altman method. Measures were taken within a 2-week interval before participants commenced an intervention program. 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 for the for MAL-AOU (r = 0.70 to 0.85) and the MAL-QOM (r = 0.61 to 0.71).

Uswatte et al. (2005b) examined 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 MAL-14 in a sample of 41 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 their caregivers, 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. 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 for patient MAL-QOM scores (r = 0.91), and adequate for patient MAL-AOU scores (r = 0.44), and caregiver MAL-AOU and MAL-QOM scores (r = 0.61, r = 0.50 respectively).

Uswatte et al. (2006b) examined 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 MAL-30 in a sample of 116 patients with subacute/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 their caregivers, using Intra Class Coefficients (ICC). 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 the MAL-AOU and MAL-QOM was excellent among patients (ICC = 0.79, ICC = 0.82, respectively), and adequate among caregivers (ICC = 0.66, ICC = 0.72, respectively). There was a trend toward an increase from test 1 to test 2 among both patients and caregivers (patient MAL-AOU: 0.3 ± 0.6, p = 0.04; patient MAL-QOM: 0.3 ± 0.5, p = 0.02; caregiver MAL-AOU: 0.4 ± 0.7, p = 0.05; caregiver MAL-QOM: 0.4 ± 0.7, p = 0.02), although increases were less than the minimal clinically important difference (< 0.5 points).

Huseyinsinoglu et al. (2011) examined 3-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 MAL-28 (Turkish version) in a sample of 30 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 intraclass coefficients (ICC) and Spearman 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. 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 for the MAL-AOU (ICC = 0.97, r = 0.94) and the MAL-QOM (ICC = 0.96, r = 0.93).

Saliba et al. (2011) examined 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 MAL (Brazilian version), using intra-class 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 (ICC). 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 the MAL-AOU and MAL-QOM was excellent (ICC = 0.98).

Taub et al. (2013) reported on 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 Grade 4/5 MAL, referencing unpublished data from Morris (2009) that used a sample of 10 individuals 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.. 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 the Grade 4/5 MAL was excellent (r = 0.95).

Intra-rater:
No studies have reported on the 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 MAL.

Inter-rater:
Uswatte et al. (2005b) examined 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 MAL-14 in a sample of 41 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 their caregivers using Intra Class Coefficients (ICC). Participants received Constraint-Induced Movement Therapy (CIMT) or time-matched general fitness rehabilitation for two weeks. 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 .
between patient and carer pre-treatment scores was adequate (ICC = 0.52, p < 0.01); 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 .
between patient and carer change scores following treatment was adequate (ICC = 0.7, p < 0.0001).

Validity

Content:

No studies have reported on 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 MAL.

Criterion:

Concurrent:
Johnson et al. (2003) examined 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 MAL-45 in a sample of 12 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. by comparison with the Abilhand, 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. Correlations with the Abilhand were excellent for the MAL-AOU (r = 0.71, p < 0.05) and MAL-QOM (r = 0.88, p < 0.05).

Uswatte et al. (2005b) examined 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 MAL-14 (QOM scale only) in a sample of 27 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. by comparison with accelerometry of the affected arm, 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. Correlations between the MAL-QOM and accelerometer recordings at pre-treatment (r = 0.70, p < 0.05) were excellent. Correlations between MAL-QOM change scores from pre-treatment to post-treatment and corresponding change scores on accelerometer readings were also excellent (r = 0.91, p < 0.01).

Lin et al. (2010a) examined 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 MAL-30 by comparison with the Nine Hole Peg Test (9HPT), the Box and Block Test (BBT) and the Action Research Arm Test (ARAT), 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.
coefficients. 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. (n=59) were randomized to receive distributed constraint-induced movement therapy, bilateral arm training or neurodevelopmental therapy, and measures were taken at baseline and post-treatment (3 weeks). Correlations at baseline and post-treatment were significant and adequate with the BBT (MAL-AOU: r = 0.37, r = 0.49; MAL-QOM: r = 0.52, r = 0.52) and the ARAT (MAL-AOU: r = 0.31, r = 0.32; MAL-QOM: r = 0.39, r = 0.35). Correlations with the 9HPT were significant for the MAL-QOM only (r = -0.26, r = -0.33).

Lin et al. (2010b) examined 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 MAL-30 by comparison with 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. Impact Scale 3.0 (SIS) and the Stroke-Specific Quality of Life Scale (SS-QOL), 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.
coefficients. 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. (n = 74) were randomized to receive distributed constraint-induced movement therapy, bilateral arm training or neurodevelopmental therapy, and measures were taken at baseline and post-treatment (3 weeks). There were significant poor to adequate correlations between the MAL-AOU and most SIS domains at baseline (r = 0.24-0.58) and post-treatment (r = 0.24-0.59). There were significant excellent correlations between the MAL-QOM and the SIS – Hand function domain at baseline (r = 0.65) and post-treatment (r = 0.68), and significant poor to adequate correlations between the MAL-QOM and most other SIS domains at baseline (r = 0.26-0.52) and post-treatment (r = 0.28-0.51). There were significant correlations between the MAL-AOU and some SS-QOL domains at baseline (r = 0.25-0.37) and post-treatment (r = 0.24-0.35), and between the MAL-QOM and some SS-QOL domains at baseline (r = 0.28-0.38) and post-treatment (r = 0.26-0.39).

Wu et al. (2011) examined 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 MAL-30 in a sample of 77 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. by comparison with a modified version of the Nottingham Extended ADL Scale (NEADL) and the 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), 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.
coefficients. Measures were taken at pre-treatment and 3 weeks later at post-treatment. Correlations with the NEADL were poor to adequate (MAL-AOU: r = 0.3; MAL-QOM: r = 0.2-0.3). Correlations with the FAI were adequate (MAL-AOU: r = 0.3-0.4); MAL-QOM: r = 0.3).

Khan et al. (2013) examined cross-sectional 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 MAL-30 (German version) by comparison with the Wolf Motor Function Test (WMFT) – Time and Functional ability subtests, the Chedoke McMaster 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. Assessment (CMSA) – Arm and Hand subtests, the grip strength scale, and isometric strength measured by handheld dynamometer (mean of shoulder and elbow flexion and extension), 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.
coefficients. Patients with acute to 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. (n = 42) received inpatient rehabilitation and measures were taken at baseline; discharge from hospital and at 6-month follow-up. Significant negative correlations were seen with the WMFT – Time scores (MAL-AOU r = -0.747 – -0.878; MAL-QOM r = -0.770 – -0.901). Correlations were excellent at all time points with the WMFT – Functional ability (MAL-AOU r = 0.769 – 0.808, MAL-QOM r = 0.789 – 0.837), the CSMA – Arm (MAL-AOU r = 0.680 – 0.765; MAL-QOM r = 0.691 – 0.798) and CSMA – Hand (MAL-AOU r = 0.692 – 0.801; MAL-QOM r = 0.717 – 0.803), grip strength (MAL-AOU r = 0.698 – 0.716; MAL-QOM r = 0.659-.0733) and isometric strength (MAL-AOU r = 0.643-0.719; MAL-QOM r = 0.714-0.726).

Predictive:
No studies have examined 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 MAL.

Construct:

Uswatte et al. (2006b) conducted item analysis of the original MAL-30 using item-total correlations, 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 proportion of missing data (with an a priori cut-off of 20%) in a sample of 222 patients with subacute/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 their caregivers. Of the 30 items, 25 items were completed by > 80% of caregivers and 28 items were completed by > 80% of patients; analysis of these 28 items indicated item-total correlations > 0.5 for 92% of items, and 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 .
coefficients > 0.5 for 89% of items. The remaining 2 items (write on paper: 48% missing data; put makeup/shaving cream on face: 20% missing data) showed lower item-total correlations and 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 .
coefficients and were dropped accordingly.

van der Lee et al. (2004) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-14 in a sample of 56 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 Spearman’s 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 an excellent 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 MAL-AOU and MAL-QOM (r = 0.95, p < 0.001).

Uswatte et al. (2005b) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-14 (QOM scale only) in a sample of 27 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. by comparison with patient/caregiver MAL-AOU scores, 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. Correlations were excellent between MAL-QOM change scores from pre-treatment to post-treatment and corresponding change scores in patient MAL-AOU (r = 0.80, p < 0.01), carer MAL-AOU (r = 0.73, p < 0.01) and carer MAL-QOM (r = 0.70, p < 0.01).

Uswatte et al. (2006a) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-30 in a sample of 169 individuals with subacute/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 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. There was an excellent 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 MAL-AOU and MAL-QOM (r = 0.92, p < 0.001).

Huseyinsinoglu et al. (2011) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-28 (Turkish version) in a sample of 30 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 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 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 MAL-AOU and the MAL-QOM was excellent (r = 0.95).

Saliba et al. (2011) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL (Brazilian version) in a sample of 77 individuals 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 Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. There was an excellent 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 MAL-AOU and the MAL-QOM (r = 0.97, p < 0.0001).

Khan et al. (2013) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-30 (German version), 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.
coefficients. Patients with acute to 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. (n = 42) received inpatient rehabilitation and measures were taken at baseline, discharge from hospital and at 6-month follow-up. There was an excellent 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 MAL-AOU and MAL-QOM at all timepoints (r = 0.994, 0.982, 0.980).

Chuang et al. (2017) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-30 in a sample of 403 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. with motor recovery of the proximal and distal upper limb at Brunnstrom stage III and higher, using Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. 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 MAL-AOU and MAL-QOM was adequate (r = 0.603), indicating that the subscales are not highly correlated and can be perceived as different concepts.

Chuang et al. (2017) examined construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the LF-MAL in a sample of 134 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. with motor recovery of the proximal and distal upper limb at Brunnstrom stage III and lower, using Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. 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 LF-MAL-AOU and LF-MAL-QOM was adequate (r = 0.607), indicating that the subscales are not highly correlated and can be perceived as different concepts.

Convergent/Discriminant:
van der Lee et al. (2004) examined cross-sectional 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 MAL-14 by comparison with the Action Research Arm Test (ARAT) in a sample of 56 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 Spearman’s 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 were excellent correlations between the MAL-AOU and the ARAT (r = 0.63, p < 0.001) and between the MAL-QOM and the ARAT (r = 0.63, p < 0.001).

Uswatte et al. (2005a) examined 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 MAL-14 in a sample of 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. by comparison with accelerometry of the affected arm, using Spearman rank correlations. There was an excellent 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 MAL-14 and accelerometry (r = 0.74, p < 0.001).

Uswatte et al. (2006a) examined 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 MAL-30 (QOM scale only) in a sample of 169 patients with subacute/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. by comparison with accelerometry of the affected arm and the Actual Amount of Use Test (AAUT), 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. Correlations between the MAL-QOM and accelerometry ratios (ratio summary variable, impaired arm summary variable) were adequate (r = 0.52, r = 0.41 respectively, p < 0.001). 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 the MAL-QOM and AAUT was excellent (r = 0.94, p < 0.001).

Uswatte et al. (2006b) examined 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 MAL-30 in a sample of 222 patients with subacute/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 their caregivers by comparison with accelerometry of the affected arm, and the SIS 2.0 – Hand function scale, 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. Comparison of the MAL with accelerometry ratios showed adequate to excellent correlations for patient scores (MAL-AOU: r = 0.47; MAL-QOM: r = 0.52, p < 0.01), and adequate correlations for caregiver scores (MAL-AOU: r = 0.57; MAL-QOM, r = 0.61, p < 0.01). Comparison of the MAL and SIS – Hand function scores showed excellent correlations for patient scores (MAL-AOU: r = 0.68; MAL-QOM: r = 0.72, p < 0.01), and adequate correlations for caregiver scores (MAL-AOU: r = 0.35, MAL-QOM: r = 0.40, p < 0.01).

Uswatte et al. (2006b) examined divergent validityThe degree to which an assessment measures what it is supposed to measure.
of the MAL-30 in a sample of 222 patients with subacute/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 their caregivers by comparison with accelerometry of the less affected arm, and the SIS 2.0 – Mobility scale, 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. Comparison of the MAL with accelerometry ratios of the less affected arm showed poor correlations for patient scores (MAL-AOU: r = 0.14; MAL-QOM: r = 0.14, p > 0.05), and poor to adequate correlations for caregiver scores (MAL-AOU: r = 0.25; MAL-QOM, r = 0.23, p < 0.001). Comparison of the MAL and SIS – Mobility scores showed poor correlations for patient scores (MAL-AOU: r = 0.14; MAL-QOM: r = 0.14, p > 0.05), and poor correlations for caregiver scores (MAL-AOU: r = 0.10, MAL-QOM: r = 0.07, p > 0.05).

Hammer and Lindmark (2010) examined cross-sectional 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 MAL-30 by comparison with the FMA-UE, ARAT, Motor Assessment Scale – Upper Extremity score (MAS-UE), 16-hole peg test (16HPT) and the Grippit ratio of isometric grip strength, using Spearman’s 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. 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. (n = 30) were randomized to receive forced use therapy or standard upper limb rehabilitation, and measures were taken at baseline, post-treatment (2 weeks) and follow-up (3 months). Correlations were significant and adequate with all measures: FMA-UE (r = 0.43-0.52); ARAT (r = 0.31-0.51); MAS-UE (r = 0.41-0.54); 16HPT (r = -0.41 – -0.67); Grippit (r = 0.41-0.53).

Huseyinsinoglu et al. (2011) examined 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 MAL-28 (Turkish version) by comparison with the WMFT – Performance Time (WMFT-PT) and – Functional Ability (WMFT-FA) scores in a sample of 30 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 were excellent correlations with the WMFT-FA (MAL-AOU, r=0.63; MAL-QOM: r = 0.63), and adequate negative correlations with the WMFT-PT (MAL-AOU: r = -0.56; MAL-QOM: r = -0.55).

Saliba et al. (2011) examined 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 MAL (Brazilian version) by comparison with grip strength of the more severely affected upper limb in a sample of 77 individuals 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 Rasch analysisRasch analysis is a statistical measurement method that allows the measurement of an attribute – such as upper limb function – independently of particular tests or indices.   It creates a linear representation using many individual items, ranked by item difficulty (e.g. picking up a very small item, versus a task requiring a very gross grasp) and person ability.   A well performing Rasch model will have items hierarchically placed from simple to more difficult, and individuals with high abilities should be able to perform all the items below a level of difficulty.  The Rasch model is statistically strong because it enables ordinal measures to be converted into meaningful interval measures. It also allows information from various tests or tools with different scoring systems to be applied using the Rasch model.
. There were adequate correlations between grip strength and the MAL-AOU (r = 0.51, p < 0.0001) and the MAL-QOM (r =0 .57, p < 0.0001).

Sterr et al. (2014) examined divergent validityThe degree to which an assessment measures what it is supposed to measure.
of the MAL in a sample of 65 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. by comparison with the Short Form 36 (SF-36), 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. Impact Scale (SIS), Hospital Anxiety and DepressionIllness involving the body, mood, and thoughts, that affects the way a person eats and sleeps, the way one feels about oneself, and the way one thinks about things. A depressive disorder is not the same as a passing blue mood or a sign of personal weakness or a condition that can be wished away. People with a depressive disease cannot merely “pull themselves together” and get better. Without treatment, symptoms can last for weeks, months, or years. Appropriate treatment, however, can help most people with depression.
Scale (HADS) and Visual Analog Mood Score (VAMS), using regression analysis. Participants received four different Constraint-Induced Movement Therapy (CIMT) treatment protocols that differed in intensity and use of a constraint. Following treatment there was a significant positive association between the MAL-AOU and the SF-36 Physical domain (r = 0.38m p = 0.025) and a trend towards a moderate association with the SIS Total score (r = 0.43, p = 0.061).

Shindo et al. (2015) examined 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 MAL-14 in a sample of 34 patients with acute/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. by comparison with the Simple Test for Evaluating Hand Function (STEF), using Spearman’s 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 a significant and excellent 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 assessments (MAL-AOU: r = 0.805; MAL-QOM: r = 0.768).

Simpson, Conroy & Beaver (2015) examined 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 MAL-28 in a sample of 9 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 comparison with the FMA, Wolf Motor Function Test 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. Impact Scale, using Spearman’s 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 were excellent correlations between baseline MAL-AOU and FMA (ρ = 0.6889, p < 0.0132) and MAL-QOM and FMA (ρ = 0.7276, p < 0.0073).

Moreira Silva et al. (2018) examined 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 MAL-30 in a sample of 66 individuals 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. by comparison with the FMA-UE, using Spearman’s 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 a significant and excellent 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 FMA-UE (MAL-AOU: r = 0.87; MAL-QOM: r = 0.87).

Chen et al. (2018) examined 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 MAL in a sample of 82 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 comparison with accelerometry of the affected arm, using Pearson’s 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 an adequate 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 accelerometry (MAL-AOU: r = 0.47; MAL-QOM: r = 0.57).

Known Group:
Uswatte et al. (2006b) examined known-group validityThe degree to which an assessment measures what it is supposed to measure.
of the MAL in a sample of 222 patients with subacute/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 their caregivers. Correlations between the MAL and accelerometry ratio was stronger among patients with paresis of their dominant arm (MAL-AOU: r = 0.56; MAL-QOM: r = 0.59) than among patients with paresis of the non-dominant arm (MAL-AOU: r = 0.28; MAL-QOM: r = 0.34).

Responsiveness

Taub et al. (1993) reported on Effect sizes (ES) of the MAL in a sample of 9 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 received two weeks of upper extremity restraint and measures were taken at baseline, post-treatment and follow-up (1 month, 2 years). Effect sizes were large from baseline to 1-month follow-up (2.80) and from baseline to 2-year follow-up (2.95).

Kunkel et al. (1999) reported on ES of the MAL in a sample of 5 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 received two weeks of Constraint-Induced Movement Therapy (CIMT) and measures were taken at baseline, post-treatment and follow-up (3 months). Effect sizes were large from baseline to post-treatment (MAL-AOU: 9.57; MAL-QOM: 3.24), and from baseline to 3-month follow-up (MAL-AOU: 7.59; MAL-QOM: 1.99).

Taub et al. (1999) reported on ES of the MAL in 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. who received CIMT and reported 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”.
for lower-functioning individuals (n = 11, d = 4.0) and higher functioning individuals (n = 40, d = 3.3). The ES was larger for lower-functioning patients due to lower variability in scores from baseline to post-treatment.

Miltner et al. (1999) reported on ES of the MAL in a sample of 15 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 received two weeks of CIMT and measures were taken at baseline, post-treatment and follow-up (4 weeks and 6 months). Effect sizes were large from first contact to post-treatment (MAL-AOU: 2.07; MAL-QOM: 1.33), from first contact to 4 weeks post-treatment (MAL-AOU: 2.98; MAL-QOM: 1.70), and from first contact to 6-month follow-up (MAL-AOU: 2.68; MAL-QOM: 2.14).

van der Lee et al. (1999) reported on ES of the MAL in a sample of 66 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 randomly assigned to receive forced manual therapy or bimanual training based on neurodevelopmental techniques for two weeks. A 25-item modified version of the MAL was used. There were no significant between-group differences in MAL-QOM scores following treatment. There was a significant difference in MAL-AOU scores, in favour of forced use therapy. The mean difference in gain was 0.52 points (95% CI, 0.11-0.93). Improvements exceeded the Minimal Clinically Important Difference of 0.50 within both groups. The treatment effect was clinically relevant for patients with hemineglect.

van der Lee et al. (2004) examined responsivenessThe ability of an instrument to detect clinically important change over time.
and longitudinal construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-14 in a sample of 56 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. who were randomized to receive CIMT or bimanual training for a 2-week intervention period. ResponsivenessThe ability of an instrument to detect clinically important change over time.
was measured by responsivenessThe ability of an instrument to detect clinically important change over time.
ratios (RR). Results showed adequate responsivenessThe ability of an instrument to detect clinically important change over time.
for the MAL-AOU and MAL-QOM (RR = 1.9, 2.0 respectively). Longitudinal validityLongitudinal validity is the extent to which changes on one measure will correlate with changes on another measure.
was measured by comparing MAL change scores with the Action Research Arm Test (ARAT) change scores and a global change rating (GCR), using Spearman’s 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. Change scores between measures were not significant nor highly correlated (MAL-AOU vs. ARAT: r = 0.16, p = 0.23; MAL-QOM vs. ARAT: r = 0.16, p = 0.25; MAL-AOU vs. GCR: r = 0.20, p = 0.15; MAL-QOM vs. GCR: r = 0.22, p = 0.10).

Uswatte et al. (2005b) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the MAL-14 in a sample of 41 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. who received CIMT or time-matched general fitness rehabilitation, and their caregivers. ResponsivenessThe ability of an instrument to detect clinically important change over time.
was measured by responsivenessThe ability of an instrument to detect clinically important change over time.
ratios (RR). Results showed high responsivenessThe ability of an instrument to detect clinically important change over time.
for patient scores (MAL-AOU: 3.2; MAL-QOM: 4.5), and caregiver scores (MAL-AOU: 4.3; MAL-QOM: 3.0).

Uswatte et al. (2005b) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the MAL-14 in a sample of 27 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. who received an automated form of constraint-induced movement therapy (AutoCITE) or general fitness rehabilitation. ResponsivenessThe ability of an instrument to detect clinically important change over time.
was measured by responsivenessThe ability of an instrument to detect clinically important change over time.
ratios; results showed high responsivenessThe ability of an instrument to detect clinically important change over time.
for the MAL-AOU and MAL-QOM (RR = 3.8, 5.0, respectively).

Hammer and Lindmark (2010) examined responsivenessThe ability of an instrument to detect clinically important change over time.
and longitudinal construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the MAL-30 in a sample of 30 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. who were randomized to receive forced use therapy or standard upper extremity rehabilitation. ResponsivenessThe ability of an instrument to detect clinically important change over time.
was measured according to 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), standard response means (SRM) and responsivenessThe ability of an instrument to detect clinically important change over time.
ratios (RR) from baseline to post-treatment (2 weeks), and from baseline to follow-up (3 months). Effect sizes for the MAL-AOU and MAL-QOM were moderate to large from baseline to post-treatment (MAL-AOU: 0.51; MAL-QOM: 0.54) and from baseline to follow-up (MAL-AOU: 1.02; MAL-QOM: 1.17), indicating 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.”
to change. Standard response means were large from baseline to post-treatment (MAL-AOU: 1.28; MAL-QOM: 1.03), and from baseline to follow-up (MAL-AOU: 1.14; MAL-QOM: 1.19). The greater SRM compared to ES reflects smaller variability in change scores than baseline scores. ResponsivenessThe ability of an instrument to detect clinically important change over time.
ratios were large from baseline to post-treatment (MAL-AOU: 1.22; MAL-QOM: 1.23) and from baseline to follow-up (MAL-AOU: 2.44; MAL-QOM: 2.69). Longitudinal construct was measured by comparison with the FMA-UE, ARAT, Motor Assessment Scale – Upper Extremity score (MAS-UE), 16-hole peg test (16HPT) and the Grippit ratio of isometric grip strength, using Spearman’s 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. Correlations with the MAS-UE were significant and adequate from baseline to follow-up (MAL-AOU r = 0.53, MAL-QOM r = 0.47); and with the FMA-UE from baseline to post-treatment (MAL-AOU r = 0.44, MAL-QOM r = 0.67) and from baseline to follow-up (MAL-AOU r = 0.39, MAL-QOM r = 0.43).

Khan et al. (2013) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the German MAL-30 in a sample of 42 patients with acute to 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 standard response mean (SRM). Participants were stratified into two groups according to level of arm and hand function using the Chedoke McMaster 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. Assessment (CSMA). Measures were taken at baseline, discharge from rehabilitation and 6-month follow-up. Change scores from the lower-function group (CSMA arm and hand score ≤ 6) revealed high responsivenessThe ability of an instrument to detect clinically important change over time.
of the MAL-AOU and MAL-QOM from baseline to discharge (SRM = 0.93, 0.94 respectively) and baseline to follow-up (SRM = 0.95. 0.98 respectively), but poor from discharge to follow-up (SRM = 0.20, 0.42 respectively). Change scores from the high-function group (CSMA arm and hand score > 6) showed high responsivenessThe ability of an instrument to detect clinically important change over time.
of the MAL-AOU and MAL-QOM from baseline to discharge (SRM = 1.43, 1.31 respectively) and from baseline to follow-up (SRM = 1.34, 1.33, respectively), but poor responsivenessThe ability of an instrument to detect clinically important change over time.
from discharge to follow-up (SRM = 0.22, 0.24 respectively). The authors concluded that the MAL is a responsive measure when the intervention period is included in the measured time interval.

Simpson & Eng (2013) conducted a literature review of upper limb assessments commonly used 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. rehabilitation, including the MAL. In studies that measured outcomes following CIMT, the observed change (i.e. patients’ perceptions of change, 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 1.6-6.2 times larger than measures of functional change such as the ARAT or WMFT. Similarly, assessments which measure perceived function in the individual’s environment require larger percentage changes than laboratory-based performance measures to surpass the measurement error. Minimal Detectable Change for the MAL-AOU ranged from 72.5% to 86.7% (90% and 95% confidence levels).

Taub et al. (2013) reported on 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) of the Lower Functioning MAL (LF-MAL) in a sample of 6 individuals 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. who used orthotics/splints and adaptive equipment outside the laboratory over 6 sessions (Phase A), then received mCIMT + neurodevelopmental therapy for 15 consecutive weekdays with continued use of assistive devicesAssistive devices are any piece of equipment that you use to make your daily activities easier to perform.
(Phase B). Effect sizes were calculated from (i) baseline to pre-mCIMT; (ii) pre-mCIMT to post-mCIMT; and (iii) baseline to post-mCIMT and were large at all timepoints (ES = 2.6, 2.1, 3.0, respectively, p < 0.002).

Sterr et al. (2014) reported on treatment effect in a sample of 65 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 received four different CIMT treatment protocols that differed in intensity and use of a constraint. Whole-group analysis showed a significant and large treatment effect from baseline to post-treatment (MAL-AOU: d = 1.19; MAL-QOM: d = 1.38); the treatment effect from post-treatment to 6-month follow-up was small but significant for the MAL-AOU only (d = 0.4). Treatment effect was not significant at 12-month follow-up. There was a significant positive association between training intensity and improvement in MAL-AOU scores.

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).
:
Chen et al. (2012) examined 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 MAL. This study used data from the EXCITE trial, in which 222 patients with subacute/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. who were randomized to receive constraint induced movement therapy (CIMT) for 2 weeks (n = 106) or no treatment (n = 116). MDC with 90% confidence intervals was calculated from pre-post test data from the control group. The MDC of the MAL-AOU was 16.8% (Standard Error of the Mean 7.2%), indicating that a change in amount of use of the affected upper limb greater than 16.8% is required so as to be 90% certain that the change is not due to measurement error. The MDC (90% CI) for the MAL-QOM was 15.4% (SEM 6.6%), indicating higher 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.”
than the MAL-AOU scale. After treatment, the CIMT group showed an 84.6% increase in MAL-AOU scores and a 72.2% increase in MAL-QOM scores. Both MAL scores exceeded the MDC and were sensitive to change in the context of this intervention.

Simpson, Conroy & Beaver (2015) examined 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 MAL-28 in a sample of 9 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 comparison with the Fugl-Meyer Assessment, the Wolf Motor Function Test 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. Iimpact Scale. Measures were taken at baseline, post-treatment and follow-up, and correlations were analysed using Spearman’s 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. Changes in MAL-AOU scores were sensitive to changes in SIS physical domain scores (ρ = 0.7342, p < 0.0243). Changes in MAL-QOM scores were sensitive to changes in WMFT Functional Ability scores (ρ = 0.6245, p < 0.0722).

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See the measure

How to obtain the Motor Activity Log?

Click here to see the Motor Activity Log manual.