Purpose
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 (SIS) is a stroke-specific, self-report, health status measure. It was designed to assess multidimensional stroke outcomes, including strength, hand function 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.
of Daily Living / Instrumental 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.
of Daily Living (ADL/IADL), mobility, communication, emotion, memory and thinking, and participationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations.. The SIS can be used both in clinical and in research settings.
In-Depth Review
Purpose of the measure
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 (SIS) is a stroke-specific, self-report, health status measure. It was designed to assess multidimensional stroke outcomes, including strength, hand function, 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.
of Daily Living / Instrumental 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.
of Daily Living (ADL/IADL), mobility, communication, emotion, memory and thinking, and participationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual's involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations.. The SIS can be used both in clinical and research settings.
Available versions
The Stroke Impact Scale was developed at the Landon Center on Aging, University of Kansas Medical Center. The scale was first published as version 2.0 by Duncan, Wallace, Lai, Johnson, Embretson, and Laster in 1999. Version 2.0 of the SIS is comprised of 64 items in 8 domains (Strength, Hand function, Activities of Daily Living (ADL)Basic tasks that involve bodily issues (bathing, dressing, toileting, transferring, continence, eating and walking) that are done on a daily basis. / Instrumental ADL, Mobility, Communication, Emotion, Memory and thinking, ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual's involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations.). Based on the results of a 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.
process, 5 items were removed from version 2.0 to create the current version 3.0 (Duncan, Bode, Lai, & Perera, 2003b).
Features of the measure
Items:
The SIS version 3.0 includes 59 items and assesses 8 domains:
- Strength – 4 items
- Hand function – 5 items
- ADL/IADL – 10 items
- Mobility – 9 items
- Communication – 7 items
- Emotion – 9 items
- Memory and thinking – 7 items
- ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations./Role function – 8 items
An extra question on 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 asks that the client rate on a scale from 0 – 100 how much the client feels that he/she has recovered from his/her 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..
To see the items of the SIS, please click here.
Instructions on item administration:
Prior to administering the SIS, the purpose statement must be read as written below. It is important to tell the respondent that the information is based on his/her point of view.
Purpose statement:
“The purpose of this questionnaire is to evaluate how 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. has impacted your health and life. We want to know from your point of view how stroke has affected you. We will ask you questions about impairments and disabilities caused by your 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., as well as how 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. has affected your quality of life. Finally, we will ask you to rate how much you think you have recovered from your stroke”.
Response sheets in large print should be provided with the instrument, so that the respondent may see, as well as hear, the choice of responses for each question. The respondent may either answer with the number or the text associated with the number (eg. “5” or “Not difficult at all”) for an individual question. If the respondent uses the number, it is important for the interviewer to verify the answer by stating the corresponding text response. The interviewer should display the sheet appropriate for that particular set of questions, and after each question must read all five choices.
Questions are listed in sections, or domains, with a general description of the type of questions that will follow (eg. “These questions are about the physical problems which may have occurred as a result of your 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.”). Each group of questions is then given a statement with a reference to a specific time period (eg. “In the past week how would you rate the strength of your…”). The statement must be repeated before each individual question. Within the measure the time period changes from one week, to two weeks, to four weeks. It is therefore important to emphasize the change in the time period being assessed for the specific group of questions.
Scoring:
The SIS is a patient-based, self-report questionnaire. Each item is rated using a 5-point Likert scaleLikert scaling is one type of response to items in a questionnaire or tool. For example, Likert scaling would have you rate an item such as “I am satisfied with the care I received” on a scale using a 1-to-5 response scale where:
• 1 = strongly disagree
• 2 = disagree
• 3 = undecided
• 4 = agree
• 5 = strongly agree
You will find various options and scaling methods for the number of response choices (1-to-7, 1-to-9, 0-to-4). Odd-numbered scales usually have a middle value that is labelled Neutral or Undecided. Some tools used forced-choice Likert scaling with an even number of responses and no middle neutral or undecided choice.. The patient rates his/her difficulty completing each item, where:
- 1 = an inability to complete the item
- 5 = no difficulty experienced at all.
Note: Scores for three items in the Emotion domain (3f, 3h, 3i) must be reversed before calculating the Emotion domain score (i.e. 1 » 5, 2 » 4, 3 = 3, 4 » 2, 5 » 1). The SIS scoring database (see link below) takes this change of direction into account when scoring. When scoring manually, use the following equation to compute the item score for 3f, 3h and 3i: Item score = 6 – individual’s rating.
A final single-item Recovery domain assesses the individual’s perception of his/her recovery from strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., measured in the form of a visual analogue scale from 0-100, where:
- 0 = no recovery
- 100 = full recovery.
Domain scores range from 0-100 and are calculated using the following equation:
- Domain score = [(Mean item score – 1) / 5-1 ] x 100
Scores are interpreted by generating a summative score for each domain using an algorithm equivalent to that used in the SF-36 (Ware & Sherbourne, 1992).
See http://www.kumc.edu/school-of-medicine/preventive-medicine-and-public-health/research-and-community-engagement/stroke-impact-scale/instructions.html to download the scoring database.
Time:
The SIS is reported to take approximately 15-20 minutes to administer (Finch, Brooks, Stratford, & Mayo, 2002).
Subscales:
The SIS 3.0 is comprised of 8 subscales or ‘Domains’:
- Strength
- Hand function
- ADL/IADL
- Mobility
- Communication
- Emotion
- Memory and thinking
- ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations.
A final single-item domain measures perceived recovery since strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. onset.
Equipment:
Only the scale and a pencil are needed.
Training:
The SIS 3.0 requires no formal training for administration (Mulder & Nijland, 2016). Instructions for administration of the SIS 3.0 are available online through the University of Kansas Medical Center SIS information page.
Alternative forms of the SIS
SIS-16 (Duncan et al., 2003a).
Duncan et al. (2003) developed the SIS-16 to address the lack of 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 differences in physical functioning in functional measures 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. outcome. Factor analysis of the SIS 2.0 revealed that the four physical domains (Strength, Hand function, ADL/IADL, Mobility) are highly correlated and can be summed together to create a single physical dimension score (Duncan et al., 1999; Mulder & Nijland, 2016). Accordingly, the SIS-16 consists of 16 items from the SIS 2.0:
- ADL/IADL – 7 items
- Mobility – 8 items
- Hand Function – 1 item.
All other domains should remain separate (Duncan et al., 1999).
SF-SIS (Jenkinson et al., 2013).
Jenkinson et al. (2013) developed a modified short form of the SIS (SF-SIS) comprised of eight items. The developers selected the one item from each domain that correlated most highly with the total domain score, through three methods: initial pilot research, validation analysis and a focus group. The final choice of questions for the SF-SIS comprised those items that were chosen by methods on 2 or more occasions. The SF-SIS was evaluated for face validityA form of content validity, face validity is assessed by having 'experts' (this could be clinicians, clients, or researchers) review the contents of the test to see if the items seem appropriate. Because this method has inherent subjectivity, it is typically only used during the initial phases of test construction.
and acceptability within a focus group of patients from acute and rehabilitation 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. settings and with multidisciplinary 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. healthcare staff. The SF-SIS has also been evaluated for content, convergent and discriminant validityMeasures that should not be related are not. Discriminant validity examines the extent to which a measure correlates with measures of attributes that are different from the attribute the measure is intended to assess.
(MacIsaac et al., 2016).
Client suitability
Can be used with:
- The SIS can only be administered to patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..
- The SIS 3.0 and SIS-16 can be completed by telephone, mail administration, by proxy, and by proxy mail administration (Duncan et al., 2002a; Duncan et al., 2002b; Kwon et al., 2006). Studies have shown potential proxy bias for physical domains (Mulder & Nijland, 2016). It is recommended that possible responder bias and the inherent difficulties of proxy use be weighed against the economic advantages of a mailed survey when considering these methods of administration.
Should not be used with:
- The SIS version 2.0 should be used with caution in individuals with mild impairment as items in the Communication, Memory and Emotion domains are considered easy and only capture limitations in the most impaired individuals (Duncan et al., 2003).
- Respondents must be able to follow a 3-step command (Sullivan, 2014).
- Time taken to administer the SIS is a limitation for individuals with difficulties with concentration, attention or fatigue 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. (MacIsaac et al., 2016).
In what languages is the measure available?
The SIS was originally developed in English.
Cultural adaptations, translations and psychometric testing have also been conducted in the following languages:
- Brazilian (Carod-Artal et al., 2008)
- French (Cael et al., 2015)
- German (Geyh, Cieza & Stucki, 2009)
- Italian (Vellone et al., 2010; Vellone et al., 2015)
- Japanese (Ochi et al., 2017)
- Korean (Choi et al., 2017; Lee & Song, 2015)
- Nigerian (Hausa) (Hamza et al., 2012; Hamza et al., 2014)
- Portuguese (Goncalves et al., 2012; Brandao et al., 2018)
- Ugandan (Kamwesiga et al., 2016)
- United Kingdom (Jenkinson et al., 2013)
The MAPI Research Institute has translated the SIS and/or SIS-16 into numerous languages including Afrikaans, Arabic, Bulgarian, Cantonese, Czech, Danish, Dutch, Farsi, Finnish, French, German, Greek, Hebrew, Hungarian, Icelandic, Italian, Japanese, Korean, Malay, Mandarin, Norwegian, Portuguese, Russian, Slovak, Spanish, Swedish, Tagalog, Thai and Turkish. Translations may not be validated.
Summary
What does the tool measure? |
Multidimentional stroke outcomes, including strength, hand function, 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. of daily living/Instrumental 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. of daily living, mobility, communication, emotion, memory, thinking and participationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations.. |
What types of clients can the tool be used for? |
Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. |
Is this a screeningTesting for disease in people without symptoms. or assessment tool? |
Assessment |
Time to administer |
The SIS takes 15-20 minutes to administer. |
Versions |
SIS 2.0, SIS 3.0, SIS-16, SF-SIS. |
Other Languages |
The SIS has been translated into several languages. Please click here to see a list of translations. |
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 .
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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.:
SIS 2.0:
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.; 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. for 5/8 domains and adequate 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 3/8 domains.
SIS 3.0:
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.; 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. for 6/8 domains and adequate 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 2/8 domains.
SIS-16:
One study reported good spread of item difficulty.
SF-SIS:
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:
SIS 2.0:
One study reported adequate to excellent test-rest 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 . in all domains except for the Emotion domain. |
ValidityThe degree to which an assessment measures what it is supposed to measure.
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Criterion :
Concurrent:
SIS 2.0:
Excellent correlations with the Barthel Index, FMA, nstrumental 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. of Daily Living (IADL) Scale, Duke Mobility Scale and Geriatric 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; adequate to excellent correlations with the FIM; adequate correlations with the NIHSS and MMSE; and poor to excellent correlations with the SF-36.
SIS 3.0:
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 SIS Hand Function and MAL-QOM; 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 SIS ADL/IADL and FIM, Barthel Index, Lawton IADL Scale; 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 SIS Strength and Motricity Index; 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 SIS Mobility and Barthel Index; adequate to 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 SIS ADL/IADL and NEADL; 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 SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. and SF-36 Social Functioning, Lawton IADL scale; 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 SIS Memory domain and MMSE; poor to adequate correlations between remaining SIS domains and FIM, NEADL, FMA, MAL-AOU, MAL-QOM, FAI.
SIS-16:
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 Barthel Index; adequate to excellent correlations with the STREAM total and subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society). scores; 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 SF-36 Physical Functioning.
Predictive:
SIS 2.0:
Physical function, Emotion and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domains were statistically significant predictors of the patient’s own assessment of recovery; SIS scores were poor predictors of mean steps per day.
SIS 3.0:
Pre-treatment SIS scores were compared with outcome measures after 3 weeks of upper extremity rehabilitation: Hand function and ADL/IADL domains showed adequate to excellent correlations with FIM, FMA, MAL-AOU, MAL-QOM, FAI, and NEADL; other domains demonstrated poor to adequate correlations with outcome measures.
SIS-16:
– Admission scores show 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 actual length of stay and 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 predicted length of stay; there was a significant correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation. with discharge destination (home/rehabilitation).
– The combination of early outcomes of MAL-QOM and SIS show high accuracy in predicting final QOL among 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..
Construct:
Convergent/Discriminant:
SIS 2.0:
Domains demonstrate adequate to excellent correlations with corresponding WHOQOL-BREF subscales and Zung’s Self-Rating 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; poor correlations between the SIS Communication domain and both WHOQOL-BREF and Zung’s Self-Rating 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; and a poor 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 SIS Physical domain and the WHOQOL Environment scores.
SIS 3.0:
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 SF-SIS, EQ-5D, mRS, BI, NIHSS, EQ-5D; moderate to excellent correlations with the EQ-VAS; and a moderate 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 SIS-VAS.
SIS 3.0 telephone survey:
Adequate to excellent correlations with the FIM and SF-36V.
SIS-16:
Adequate to excellent correlations with the WHOQOL-BREF Physical domain; poor 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 WHOQOL Social relationships domain.
SF-SIS:
Excellent correlations with the EQ-5D, mRS, BI, NIHSS, EQ-5D; moderate to excellent correlations with the EQ-VAS; and moderate 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 SIS-VAS.
Known groups:
SIS 2.0: Most domains can differentiate between patients with varying degrees 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. severity.
SIS 3.0:
Physical and ADL/IADL domains showed score discrimination and distribution for different degrees 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. severity.
SIS-16:
Can discriminate between patients of varying degrees 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. severity. |
Floor/Ceiling Effects |
Three studies have examined floor/ceiling effects of the SIS.
SIS 2.0:
Two studies reported the potential for floor effects in the domain of Hand function among patients with moderate strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. severity, and a potential for ceiling effects in the Communication, Memory and Emotion domains.
SIS 3.0:
One study reported minimal floor and ceiling effects for the Social participationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain; one study reported ceiling effects for the Hand function, Memory and thinking, Communication, Mobility and ADL/IADL domains over time.
SIS-16:
One study reported no floor effects and minimal ceiling effects. |
Does the tool detect change in patients? |
Five studies have investigated responsivenessThe ability of an instrument to detect clinically important change over time. of the SIS.
SIS 2.0:
One study reported significant change in patients’ recovery in the expected direction between assessments at 1 and 3 months, and at 1 and 6 months post-stroke, however 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 was affected by strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. severity and time of post-stroke assessment.
SIS 3.0:
– One study determined change scores for a clinically important difference (CID)Clinically Important Difference (CID) is the smallest change in a measure’s score that is perceived significant by a patient or healthcare professional. within four subscales of the Strength, ADL/IADL, Mobility, Hand function. The MDC was 24.0, 17.3, 15.1 and 25.9 (respectively); minimal CID was 9.2, 5.9, 4.5 and 17.8 (respectively).
– One study reported medium responsivenessThe ability of an instrument to detect clinically important change over time. for Hand function, 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 and SIS total score; other domains showed small responsivenessThe ability of an instrument to detect clinically important change over time. .
– One study found ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. and Recovery from 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. were the most responsive domains over the first year post-stroke; Strength and Hand function domains also showed high clinically meaningful positive/negative change.
SIS-16:
One study reported change scores of 23.1 indicated statistically significant improvement from admission to discharge, and 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 was large. |
Acceptability |
– SIS 3.0 and SIS-16 are available in proxy version. The patient-centred nature of the scale’s development may enhance its relevance to patients and assessment across multiple levels may reduce patient burden.
– Time taken to administer the SIS has been identified as a limitation.
– The SIS 2.0 should be used with caution in individuals with mild impairment as some domains only capture limitations in the most impaired individuals. |
Feasibility |
– The SIS is a patient-based self-report scale that takes 15-20 minutes to administer.
– The SIS can be administered in person or by proxy, by mail or telephone.
– The SIS does not require any formal training.
– Instructions for administration of the SIS 3.0 are available online. |
How to obtain the tool? |
Please click here to see a copy of the SIS.
|
Psychometric Properties
Overview
We conducted a literature search to identify relevant publications on the psychometric properties of the SIS. Seventeen studies were included. Studies included in this review are specific to the original English versions of the SIS version 2.0, SIS 3.0 or SIS-16.
Floor/Ceiling Effects
Duncan et al. (1999) found that SIS version 2.0 showed the potential for floor effects in the Hand function domain in the moderate stroke group (40.2%) and a possible ceiling effectA ceiling effect occurs when test items aren't challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes - the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also "floor effect." in the Communication domain for both the mild (35.4%) and moderate (25.7%) 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. groups. The highest percentage of ceiling effects for the SIS was for the Communication domain (35%) compared with a 64.6% ceiling rate for the Barthel Index (Mahoney & Barthel, 1965).
Duncan et al. (2003b) conducted a 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.
which confirmed these two effects observed in Duncan et al. (1999) – a floor effectThe floor effect is when data cannot take on a value lower than some particular number. Thus, it represents a subsample for whom clinical decline may not register as a change in score, even if there is worsening of function/behavior etc. because there are no items or scaling within the test that measure decline from the lowest possible score. See also "ceiling effect."
in the SIS Hand function domain and a ceiling effect in the Communication domain. A ceiling effectA ceiling effect occurs when test items aren't challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes - the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also "floor effect." in the Memory and Emotion domains was also reported.
Lai et al. (2003) examined floor/ceiling effects of the SIS-16 and SIS Social Participation domain in a sample of 278 patients at 3 months post-stroke. The authors reported floor/ceiling effects of 0% and 4% (respectively) for the SIS-16, and 1% and 5% (respectively) for the SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual's involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain.
Richardson et al. (2016) examined floor/ceiling effects of the SIS 3.0 in a sample of 164 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.. Measures were taken at three timepoints: on admission to the study and at 6-month and 12-month follow-up (n=164, 108, 37 respectively). Poor ceiling effects (>20%) were seen for the Hand function domain at baseline, 6 months and 12 months (25.0%, 36.4%, 37.8%, respectively); the Memory and thinking domain at 6 months and 12 months (22.2%, 21.6%, respectively); the Communication domain at 6 months and 12 months (30.6%, 27%, respectively); the Mobility domain at 6 months (20.4%); and the ADL/IADL domain at 12 months (21.6%). There were no significant floor effects at any timepoint.
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.:
Duncan et al (1999) 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 SIS version 2.0 using Cronbach’s alpha coefficients and 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. for each of the 8 domains (ranging from a=0.83 to 0.90).
Duncan et al. (2003b) 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 SIS version 2.0 by 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.
. Item separation 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 .
is the ratio of the “true” (observed minus error) variance to the obtained variation. The smaller the error, the higher the ratio will be. It ranges from 0.00 to 1.00 and is interpreted the same as the Cronbach’s alpha. Item separation 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 SIS version 2.0 ranged from 0.93-1.00. A separation index > 2.00 is equivalent to a Cronbach’s alpha of 0.80 or greater (excellent). In this study, 5 out of 8 domains had a separation index that exceeded 2.00 (in addition to the composite physical domain). The values for the Emotion and Communication domains were only in the adequate range because of the ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” in those domains and those for the Hand function domain were only adequate because of the floor effectThe floor effect is when data cannot take on a value lower than some particular number. Thus, it represents a subsample for whom clinical decline may not register as a change in score, even if there is worsening of function/behavior etc. because there are no items or scaling within the test that measure decline from the lowest possible score. See also “ceiling effect.”
in that domain.
Edwards and O’Connell (2003) administered the SIS version 2.0 to 74 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. and 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. (ranging from a=0.87 for participationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. to a=0.95 for hand function). The percentage of item-domain correlations >0.40 was 100% for all domains except emotion and ADL/IADL. In the ADL/IADL scale, one item (cutting food) was more closely associated with hand function than ADL/IADL.
Lai et al. (2003) 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 SIS-16 and SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain in a sample of 278 patients at 3 months post-stroke. Both the SIS-16 and SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain showed good spread of item difficulty, with easier items that are able to measure lower levels of physical functioning in patients with severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..
Jenkinson 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 SIS 3.0 and the SF-SIS among 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. (n=73, 151 respectively), 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. of the SIS 3.0 was excellent for all domains (a=0.86 to 0.96). Higher order factor analysis of the SIS 3.0 showed one factor with an eigenvalue > 1 that accounted for 68.76% of the variance. Each dimension of the SIS 3.0 loaded on this factor (eigen value = 5.5). 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 SF-SIS was high (a=0.89). Factor analysis of the SF-SIS similarly showed one factor that accounted for 57.25% of the variance.
Richardson et al. (2016) 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 SIS 3.0 in a sample of 164 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., 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 measured at three timepoints: on admission to the study and at 6-month and 12-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. of all domains was excellent at all timepoints (a=0.81 to 0.97). The composite Physical Functioning score was excellent at all timepoints (a=0.95 to 0.97).
MacIsaac et al. (2016) 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 SIS 3.0 in a sample of 5549 individuals in an acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. setting and 332 individuals in a 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 setting, 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 within both acute and rehabilitation data sets (a=0.98, 0.93 respectively). 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 individual domains was excellent for both acute and rehabilitation data sets, except for the Emotion domain (a=0.60, 0.63 respectively) and the Strength domain (a=0.77, rehabilitation data set only).
Test-retest:
Duncan 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 SIS version 2.0 in 25 patients who were administered the SIS at 3 or 6 months post 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 again one week later. Test-retest was calculated using intraclass correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficients (ICC), which ranged from adequate to excellent (ICC=0.7 to 0.92) with the exception of the Emotion domain, which had only a poor 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.
(ICC=0.57).
Validity
Content:
Development of the SIS was based on a study at the Landon Center on Aging, University of Kansas Medical Center (Duncan, Wallace, Studenski, Lai, & Johnson, 2001) using feedback from individual interviews with patients and focus group interviews with patients, caregivers, and health care professionals. Participants included 30 individuals with mild and moderate strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain., 23 caregivers, and 9 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. experts. Qualitative analysis of the individual and focus group interviews generated a list of potential items. Consensus panels reviewed the potential items, established domains for the measure, developed item scales, and decided on mechanisms for administration and scoring.
Criterion:
Concurrent:
Duncan et al. (1999) 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 SIS by comparison with the Barthel Index, Functional Independence Measure (FIM), Fugl-Meyer Assessment (FMA), Mini-Mental State Examination (MMSE), National Institute of Health 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 (NIHSS), Medical Outcomes Study Short Form 36 (SF-36), Lawton Instrumental Activities of Daily Living (IADL)Complex tasks that involve social or societal issues (shopping, bill paying, cooking, housework, etc.) that are done on a regular basis. Scale, Duke Mobility Scale and Geriatric 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. The following results were found for each domain of the SIS:
SIS Domain |
Comparative Measure |
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.
|
Rating |
Hand function |
FMA – Upper Extremity Motor |
r = 0.81 |
Excellent |
Mobility |
FIM Motor |
r = 0.83 |
Excellent |
Barthel Index |
r = 0.82 |
Excellent |
Duke Mobility Scale |
r = 0.83 |
Excellent |
SF-36 Physical Functioning |
r = 0.84 |
Excellent |
Strength |
NIHSS Motor |
r = -0.59 |
Adequate |
FMA Total |
r = 0.72 |
Excellent |
ADL/IADL |
Barthel Index |
r = 0.84 |
Excellent |
FIM Motor |
r = 0.84 |
Excellent |
Lawton IADL Scale |
r = 0.82 |
Excellent |
Memory |
MMSE |
r = 0.58 |
Adequate |
Communication |
FIM Social/Cognition |
r = 0.53 |
Adequate |
NIHSS Language |
r = -0.44 |
Adequate |
Emotion |
Geriatric 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 |
r = -0.77 |
Excellent |
SF-36 Mental Health |
r = 0.74 |
Excellent |
ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. |
SF-36 Emotional Role |
r = 0.28 |
Poor |
SF-36 Physical Role |
r = 0.45 |
Adequate |
SF-36 Social Functioning |
r = 0.70 |
Excellent |
Physical |
Barthel Index |
r = 0.76 |
Excellent |
FIM Motor |
r = 0.79 |
Excellent |
SF-36 Physical Functioning |
r = 0.75 |
Excellent |
Lawton IADL Scale |
r = 0.73 |
Excellent |
Duncan et al. (2002a) 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 SIS version 3.0 and SIS-16 using Pearson correlations. The SIS was correlated with the Mini-Mental State Examination (MMSE), Barthel Index, Lawton IADL Scale and the Motricity Index. The SIS ADL/IADL domain showed 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 the Barthel Index (r=0.72) and with the Lawton IADL Scale (r=0.77). The SIS Mobility domain showed 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 the Barthel Index (r=0.69). The SIS Strength domain showed 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 the Motricity Index (r=0.67). The SIS Memory domain showed 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 the MMSE (r=0.42).
Lai 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 SIS-16 and SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain by comparison with the SF-36 Physical Functioning and Social Functioning subscales, Barthel Index and Lawson IADL 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. Measures were administered to 278 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. at 3 months post-stroke. 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.
between SIS-16 and SF-36 Physical Functioning (r=0.79), and 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 SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. and SF-36 Social Functioning (r=0.65). 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 SIS-16 and the Barthel Index at 3 months post-stroke (r=0.75), and 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 SIS Social ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. and Lawton IADL Scale at 3 months post-stroke (r=0.47).
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 SIS version 3.0 by comparison with the Fugl-Meyer Assessment (FMA), Motor Activity Log – Amount of Use and – Quality of Movement (MAL-AOU, MAL-QOM), Functional Independence Measure (FIM), 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) and Nottingham Extended 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.
of Daily Living Scale (NEADL). 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.”
was measured using 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 prior to and on completion of a 3-week intervention period. SIS Hand Function showed 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 MAL-QOM at pre-treatment and post-treatment (r=0.65, 0.68, respectively, p<0.01), and adequate correlations with all other measures (FMA, MAL-AOU, FIM, FAI, NEADL). SIS ADL/IADL showed 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 the FIM at pre-treatment and post-treatment (r=0.69, 0.75, respectively, p<0.01). Correlations between SIS ADL/IADL and the NEADL were adequate at pre-treatment (r=0.54, p<0.01) and excellent at post-treatment (r=0.62, p<0.01). Correlations between the SIS ADL-IADL and all other measures (FMA, MAL-AOU, MAL-QOM, FAI) were adequate at pre-treatment and post-treatment. Other SIS domains demonstrated poor to adequate correlations with comparison measures.
Ward 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 SIS-16 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. Rehabilitation Assessment of Movement (STREAM), using Spearman correlations. Measures were administered to 30 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. on admission to and discharge from an acute rehabilitation setting. Correlations between the SIS-16 and STREAM total and subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
scores were adequate to excellent on admission (STREAM total r=0.7073; STREAM subtests r=0.5992 to 0.6451, p<0.0005) and discharge (STREAM total r=0.7153; STREAM subtests r=0.5499 to 0.7985, p<0.0002).
Richardson et al. (2016) 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 SIS 3.0 by comparison with the 5-level EuroQol 5D (EQ-5D-5L), 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. Measures were administered to 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. on admission to the study and at 6-month and 12-month follow-up (n=164, 108, 37, respectively). At admission correlations with the EQ-5D-5L were excellent for the ADL (r=0.663) and Hand function (r=0.618) domains and Physical composite score (r=0.71); correlations with other domains were adequate (r=0.318 to 0.588), except for the Communication domain (r=0.228). At 6-month follow-up correlations with the EQ-5D-5L were excellent for the Strength (r=0.628), ADL (r=0.684), Mobility (r=0.765), Hand function (r=0.668), ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. (r=0.740) and Recovery domains (r=0.601) and Physical composite score (r=0.772); correlations with other domains were adequate (r=0.402 to 0.562). At 12-month follow-up correlations with the EQ-5D-5L were excellent for the Strength (r=0.604), ADL (r=0.760), Mobility (r=0.683) and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. (r=0.738) domains and the Physical composite score (r=756); correlations with other domains were adequate (r=0.364 to 0.592).
Predictive:
Duncan et al. (1999) examined which domain scores of the SIS version 2.0 could most accurately predict a patient’s own assessment 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, using multiple regression analysis. The SIS domains of Physical function, Emotion, and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual's involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. were found to be statistically significant predictors of the patient’s assessment of recovery. Forty-five percent of the variance in the patient’s assessment of percentage of recovery was explained by these factors.
Fulk, Reynolds, Mondal & Deutsch (2010) examined the predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the 6MWT and other widely used clinical measures (FMA-LE, self-selected gait-speed, SIS and BBS) in 19 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. The SIS was found to be a poor predictor of mean steps per day (r=0.18, p=0.471). Although gait speed and balance were related to walking activity, only the 6MWT was found to be a predictor of community ambulation in patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain..
Huang et al. (2010) examined change in quality of life after distributed constraint-induced movement therapy (CIMT) in a sample of 58 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 CHAID analysis. Predictors of change included age, gender, side of lesion, time since 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., cognitive status (measured by the MMSE), upper extremity motor impairmentLoss of strength and coordination, decrease in arm or leg movement
(measured by the FMA-UE) and independence in 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.
of daily living (measured by the FIM). Initial FIM scores were the strongest predictor of overall SIS score (p=0.006) and ADL/IADL domain score (p=0.004) at post-treatment. Participants with FIM scores ≤ 109 showed significantly greater improvement in overall SIS scores than participants with FIM scores > 109. There were no significant associations between other SIS domains and other predictors.
Lin et al. (2010a) 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 SIS version 3.0 by comparing pre-treatment SIS scores with post-treatment scores of the Fugl-Meyer Assessment (FMA), Motor Activity Log – Amount of Use and – Quality of Movement (MAL-AOU, MAL-QOM), Functional Independence Measure (FIM), 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) and Nottingham Extended 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.
of Daily Living Scale (NEADL). 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.
was measured using 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 prior to and on completion of a 3-week intervention period. The SIS Hand Function showed excellent correlations with MAL-AOU (r=0.61, p<0.01) and MAL-QOM (r=0.66, p<0.01), and adequate correlations with all other measures (FMA, FIM, FAI, NEADL). The SIS ADL/IADL showed 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 the FIM (r=0.70, p<0.01), and adequate correlations with all other measures (FMA, MAL-AOU, MAL-QOM, FAI, NEADL). Other SIS domains demonstrated poor to adequate correlations with comparison measures.
Ward et al. (2011) 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 SIS-16 and other clinical measures (STREAM, FIM) in a sample of 30 patients in an acute rehabilitation setting, using Spearman rho coefficients and Wilcoxon rank-sum tests. Results indicated 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 SIS-16 admission scores and predicted length of stay (rho=-0.6743, p<0.001) and 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 SIS-16 admission scores and actual length of stay (rho=-0.7953, p<0.001). There was an significant correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases - for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases - for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
with discharge destination (p<0.05).
Lee et al. (2016) developed a computational method to predict quality of life after strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. rehabilitation, using Particle Swarm-Optimized Support Vector Machine (PSO-SVM) classifier. A sample of 130 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. received occupational therapy for 1.5-2 hours/day, 5 days/week for 3-4 weeks. Predictors of outcome included 5 personal parameters (age, gender, time since strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. onset, education, MMSE score) and 9 early functional outcomes (Fugl-Meyer Assessment, Wolf Motor Function Test, Action Research Arm Test, Functional Independence Measure, Motor Activity Log – Amount of Use (MAL-AOU) and – Quality of Movement (MAL-QOM), ABILHAND, physical function, SIS). The combination of early outcomes of MAL-QOM and SIS showed highest accuracy (70%) and highest cross-validated accuracy (81.43%) in predicting final QOL among 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.. SIS alone showed high accuracy (60%) and cross-validated accuracy (81.43%).
Construct:
Duncan et al. (2003b) performed a 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.
on version 2.0 of the SIS. For measures that have been developed using a conceptual hierarchy of items, the theoretical ordering can be compared with the empirical ordering produced by the 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.
as evidence of the 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 measure. In this study, the expectation regarding the theoretical ordering of task difficulty was consistent with the empirical ordering of the items by difficulty for each domain, providing evidence for the 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 SIS.
Convergent/Discriminant:
Edwards and O’Connell (2003) examined discriminant validityMeasures that should not be related are not. Discriminant validity examines the extent to which a measure correlates with measures of attributes that are different from the attribute the measure is intended to assess.
of the SIS version 2.0 and SIS-16 in a sample of 74 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 World Health Organization Quality of Life Bref-Scale (WHOQOL-BREF) and Zung’s Self-Rating 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 (ZSRDS). There were adequate to excellent correlations between the SIS-16 and the WHOQOL-BREF Physical domain (r=0.40 to 0.63); correlations with the WHOQOL-BREF Social relationships domain were poor (r=0.13 to 0.18). There were adequate to excellent correlations between the SIS ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain and all WHOQOL-BREF domains (r=0.45 to 0.69). 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 SIS ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain and the WHOQOL-BREF Physical domain was excellent (r=0.69). The SIS ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain demonstrated 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 the ZSRDS (r=-0.56). There were adequate correlations between the SIS Memory and Emotion domains and the WHOQOL-BREF Psychological domain (r=0.49, 0.70, respectively) and between the SIS Memory and Emotion domains and the ZSRDS (r=-0.38, -0.62, respectively). There was a poor 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 SIS Physical domain and the WHOQOL-BREF Environment scores (r=0.15). Neither the ZSRDS nor the WHOQOL-BREF assess communication, accordingly both measures demonstrated poor correlations with the SIS Communication domain (ZSRDS: r=-0.28; WHOQOL-BREF: r=0.11 to 0.28).
Note: Some correlations are negative because a high score on the SIS indicates normal performance whereas a high score on other measures indicates impairment.
Jenkinson et al. (2013) 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 SIS version 3.0 and the SF-SIS in a sample of 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. (n=73, 151, respectively) by comparison with the EuroQoL EQ-5D, using Spearmans 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 SIS and SF-SIS demonstrated identical excellent correlations with the EQ-5D (r=0.83)
MacIsaac et al. (2016) 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 SIS 3.0 and the SF-SIS in a sample of 5549 patients in an acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. setting and 332 patients in a 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 setting, 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. 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.
was measured by comparison with the SIS-VAS, patient-reported outcome measures the EuroQoL EQ-5D and EQ-5D-VAS, and functional measures the Barthel Index (BI), modified Rankin Score (mRS), and the National Institutes of Health 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 (NIHSS). Within acute data, the SIS and SF-SIS demonstrated significant excellent correlations with the mRS (p=-0.87, -0.80, respectively), the BI (p=0.89, 0.80), the NIHSS (p=-0.77, -0.73), the EQ-5D (p=0.88, 0.82) and the EQ-VAS (p=0.73, 0.72). Within rehabilitation data, the SIS and SF-SIS demonstrated excellent correlations with the BI (p=0.72, 0.65, respectively) and the EQ5D (p=0.69, 0.69), and moderate correlations with the SIS-VAS (p=0.56, 0.57) and the EQ-VAS (p=0.46, 0.40). Correlations between the SIS and SF-SIS were excellent in the acute data (p=0.94) and rehabilitation data (p=0.96).
Kwon et al. (2006) 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 SIS 3.0 by telephone administration in a sample of 95 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 Pearson coefficients. 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.
was measured by comparison with the Functional Independence Measure (FIM) – Motor component (FIM-M) and – Cognitive component (FIM-C), with the Medical Outcomes Study Short Form 36 for veterans (SF-36V). Patients were administered the SIS at 12 weeks post-stroke and the FIM and SF-36 at 16 weeks post-stroke. The SIS 3.0 telephone survey showed adequate to excellent correlations with the FIM (r=0.404 to 0.858, p<0.001) and SF-36V (r=0.362 to 0.768, p<0.001).
Known groups:
Duncan et al. (1999) found that all domains of the SIS version 2.0, with the exception of the Memory/thinking and Emotion domains, were able to discriminate between patients across 4 Rankin levels 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. severity (p<0.0001, except for the Communication domain, p=0.02). These results suggest that scores from most domains of the SIS can differentiate between patients based on strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. severity.
Lai et al. (2003) administered the SIS and SF-36 to 278 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. 90 days after strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain.. The SIS-16 was able to discriminate among the Modified Rankin Scale (MRS) levels of 0 to 1, 2, 3, and 4. The SIS ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual's involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domain was also able to discriminate across the MRS levels of 0 to 1, 2, and 3 to 4. These results suggest that the SIS can discriminate between patients of varying degrees 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. severity.
Kwon et al. (2006) administered the SIS 3.0 by telephone administration to a sample of 95 patients at 12 weeks post-stroke. The MRS was administered to patients at hospital discharge. SIS 3.0 scores were reported by domains: SIS-16, SIS-Physical and SIS-ADL; all domains showed score discrimination and distribution for different degrees 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. severity: MRS 0/1 vs. MRS 4/5; MRS 2 vs. MRS 4/5; and MRS 3 vs. MRS 4/5.
Sensitivity and Specificity:
Beninato, Portney & Sullivan (2009) 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."
and specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative).
of the SIS-16 relative to a history of multiple falls 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.. Participants reported a history of no falls or one fall (n=18) vs. multiple falls (n=9), according to Tinetti’s definition of falls. SIS-16 cut-off scores of 61.7 yielded 78% 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."
and 89% specificitySpecificity refers to the probability that a diagnostic technique will indicate a negative test result when the condition is absent (true negative).
. Area under the ROC curve was adequate (0.86). Likelihood ratios were used to calculate post-test probability of a history of falls, and results showed high positive (LR+ = 7.0) and low negative (LR- = 0.25) likelihood ratios. Results indicate that the SIS-16 demonstrated good overall accuracy in detecting individuals with a history of multiple falls.
Responsiveness
Duncan et al. (1999) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the SIS version 2.0. Significant change was observed in patients’ recovery in the expected direction between assessments at 1 and 3 months, and at 1 and 6 months post-stroke, however 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 was affected by strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. severity and time of post-stroke assessment. All domains of the SIS showed statistically significant change from 1 to 3 months and 1 to 6 months post-stroke, but this was not observed between 3 and 6 months post-stroke for the domains of Hand function, Mobility, ADL/IADL, combined physical, and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. among patients recovering from minor 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.. For patients with moderate strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain., statistically significant change was observed at both 1 to 3 months and 1 to 6 months post-stroke in all domains, and from 3 to 6 months for the domains of Mobility, ADL/IADL, combined physical, and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations..
Lin et al. (2010a) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the SIS version 3.0 in a sample of 74 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 constraint-induced movement therapy (CIMT), bilateral arm training (BAT) or conventional rehabilitation over a 3-week intervention period. ResponsivenessThe ability of an instrument to detect clinically important change over time.
was measured according to change from pre- to post-treatment, using Wilcoxon signed rank test and Standardised Response Mean (SRM). Most SIS domains showed small responsivenessThe ability of an instrument to detect clinically important change over time.
(SRM = 0.22-0.33, Wilcoxon Z = 1.78-2.72). Medium responsivenessThe ability of an instrument to detect clinically important change over time.
was seen for Hand Function (SRM = 0.52, Wilcoxon Z = 4.24, P<0.05), 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 (SRM = 0.57, Wilcoxon Z = 4.56, P<0.05) and SIS total score (SRM=0.50, Wilcoxon Z = 3.89, P<0.05).
Lin et al. (2010b) evaluated the clinically important difference (CID)Clinically Important Difference (CID) is the smallest change in a measure’s score that is perceived significant by a patient or healthcare professional. within four physical domains of the SIS 3.0 (strength, ADL/IADL, mobility, hand function) in a sample of 74 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 CIMT, BAT or conventional rehabilitation over a 3-week intervention period. The following change scores were found to indicate a true and reliable improvement (MDC): Strength subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 24.0; ADL/IADL subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 17.3; Mobility subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 15.1; and Hand Function subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 25.9. The following mean change scores were considered to represent a CID: Strength subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 9.2; ADL/IADL subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 5.9; Mobility subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 4.5; and Hand Function subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
= 17.8. CID values were determined by the effect-size index and from comparison with a global rating of change (defined by a score of 10-15% in patients’ perceived overall recovery from pre- to post-treatment).
Note: Lin et al. (2010b) note that CID estimates may have been influenced by the age of participants and baseline degree of severity. Younger patients needed greater change scores from pre- to post-treatment to have a clinically important improvement compared to older patients. Those with higher baseline severity of symptoms showed greater MDC values therefore must show more change from pre- to post-treatment in order to demonstrate significant improvements. Also, the results may be limited to strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. patients who demonstrate improvement after rehabilitation therapies, Brunnstromm stage III and sufficient cognitive ability. Therefore, a larger sample size is recommended for future validation of these findings.
Ward et al. (2011) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the SIS-16 and other clinical measures (STREAM, FIM) in a sample of 30 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Change scores were evaluated using Wilcoxon signed rank test and responsivenessThe ability of an instrument to detect clinically important change over time.
to change was assessed using standardized response means (SRM). Measures were taken on admission to and discharge from an acute rehabilitation setting (average length of stay 23.3 days, range 7-53 days). SIS-16 change scores indicated statistically significant improvement from admission to discharge (23.1, p<0.0001) and 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 was large (SRM=1.65).
Guidetti et al. (2014) examined responsivenessThe ability of an instrument to detect clinically important change over time.
of the SIS 3.0 in a sample of 204 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 were assessed at 3 and 12 months post-stroke, using Wilcoxon’s matched pairs test. Clinically meaningful change within a domain was defined as a change of 10-15 points between timepoints. The ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. and Recovery domains were the most responsive domains over the first year post-stroke, with 27.5% and 29.4% of participants (respectively) reporting a clinically meaningful positive change, and 20% and 10.3% of participants (respectively) reporting a clinically meaningful negative change, from 3 to 12 months post-stroke. The Strength and Hand function domains also showed high clinically meaningful positive change (23%, 18.0% respectively) and negative change (14.7%, 14.2% respectively) from 3 to 12 months post-stroke. There were significant changes in scores on the Strength (p=0.045), Emotion (p=0.001) and Recovery (p<0.001) domains from 3 to 12 months post-stroke. The Strength, Hand function and ParticipationAs defined by the International Classification of Functioning, Disability and Health, participation is an individual’s involvement in life situations in relation to health conditions, body functions or structures, activities, and contextual factors. Participation restrictions are problems an individual may have in the manner or extent of involvement in life situations. domains had the highest perceived impact (i.e. lowest mean scores) at 3 months and 12 months.
References
- Beninato, M., Portney, L.G., & Sullivan, P.E. (2009). Using the International Classification of Functioning, Disability and Health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Physical Therapy, 89(8), 816-25.
- Brandao, A.D., Teixeira, N.B., Brandao, M.C., Vidotto, M.C., Jardim, J.R., & Gazzotti, M.R. (2018). Translation and cultural adaptation of the Stroke Impact Scale 2.0 (SIS): a quality-of-life scale for stroke. Sao Paulo Medical Journal, 136(2), 144-9. doi: 10.1590/1516-3180.2017.0114281017
- Brott, T.G., Adams, H.P., Olinger, C.P., Marler, J.R., Barsan, W.G., Biller, J., Spilker, J., Holleran, R., Eberle, R., Hertzberg, V., Rorick, M., Moomaw, C.J., & Walker, M. (1989). Measurements of acute cerebral infarction: A clinical examination scale. Stroke, 20, 864-70.
- Cael, S., Decavel, P., Binquet, C., Benaim, C., Puyraveau, M., Chotard, M., Moulin, T., Parrette, B., Bejot, Y., & Mercier, M. (2015). Stroke Impact Scale version 2: validation of the French version. Physical Therapy, 95(5), 778-90.
- Carod-Artal, F.J., Coral, L.F., Trizotto, D.S., Moreira, C.M. (2008). The Stroke Impact Scale 3.0: evaluation of acceptability, reliability, and validity of the Brazilian version. Stroke, 39, 2477-84.
- Choi, S.U., Lee, H.S., Shin, J.H., Ho, S.H., Koo, M.J., Park, K.H., Yoon, J.A., Kim, D.M., Oh, J.E., Yu, S.H., & Kim, D.A. (2017). Stroke Impact Scale 3.0: reliability and validity evaluation of the Korean version. Annals of Rehabilitation Medicine, 41(3), 387-93.
- Collin, C. & Wade, D. (1990). Assessing motor impairment after stroke: a pilot reliability study. Journal of Neurology, Neurosurgery, and Psychiatry, 53, 576-9.
- Duncan, P. W., Bode, R. K., Lai, S. M., & Perera, S. (2003b). Rasch analysis of a new stroke-specific outcome scale: The Stroke Impact Scale. Archives of Physical Medicine and Rehabilitation, 84, 950-63.
- Duncan, P. W., Lai, S. M., Tyler, D., Perera, S., Reker, D. M., & Studenski, S. (2002a). Evaluation of Proxy Responses to the Stroke Impact Scale. Stroke, 33, 2593-9.
- Duncan, P.W., Reker, D.M., Horner, R.D., Samsa, G.P., Hoenig, H., LaClair, B.J., & Dudley, T.K. (2002b). Performance of a mail-administered version of a stroke-specific outcome measure: The Stroke Impact Scale. Clinical Rehabilitation, 16(5), 493-505.
- Duncan, P.W., Wallace, D., Lai, S.M., Johnson, D., Embretson, S., & Laster, L.J. (1999). The Stroke Impact Scale version 2.0: Evaluation of reliability, validity, and sensitivity to change. Stroke, 30, 2131-40.
- Duncan, P.W., Wallace, D., Studenski, S., Lai, S.M., & Johnson, D. (2001). Conceptualization of a new stroke-specific outcome measure: The Stroke Impact Scale. Topics in Stroke Rehabilitation, 8(2), 19-33.
- Duncan, P.W., Lai, S.M., Bode, R.K., Perea, S., DeRosa, J.T., GAIN Americas Investigators. (2003a). Stroke Impact Scale-16: A brief assessment of physical function. Neurology, 60, 291-6.
- Edwards, B. & O’Connell, B. (2003). Internal consistency and validity of the Stroke Impact Scale 2.0 (SIS 2.0) and SIS-16 in an Australian sample. Quality of Life Research, 12, 1127-35.
- Finch, E., Brooks, D., Stratford, P.W., & Mayo, N.E. (2002). Physical Rehabilitations Outcome Measures. A Guide to Enhanced Clinical Decision-Making (2nd ed.), Canadian Physiotherapy Association, Toronto.
- Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189-98.
- Fugl-Meyer, A.R., Jaasko, L., Leyman, I., Olsson, S., & Steglind, S. (1975). The post-stroke hemiplegic patient: a method for evaluation of physical performance. Scandinavian Journal of Rehabilitation Medicine, 7, 13-31.
- Fulk, G.D., Reynolds, C., Mondal, S., & Deutsch, J.E. (2010). Predicting home and community walking activity in people with stroke. Archives of Physical Medicine and Rehabilitation, 91, 1582-6.
- Geyh, S., Cieza, A., & Stucki, G. (2009). Evaluation of the German translation of the Stroke Impact Scale using Rasch analysis. The Clinical Neuropsychologist, 23(6), 978-95.
- Goncalves, R.S., Gil, J.N., Cavalheiro, L.M., Costa, R.D., & Ferreira, P.L. (2012). Reliability and validity of the Portuguese version of the Stroke Impact Scale 2.0 (SIS 2.0). Quality of Life Research, 21(4), 691-6.
- Guidetti, S., Ytterberg, C., Ekstam, L., Johansson, U., & Eriksson, G. (2014). Changes in the impact of stroke between 3 and 12 months post-stroke, assessed with the Stroke Impact Scale. Journal of Rehabilitative Medicine, 46, 963-8.
- Hamilton, B.B., Granger, C.V., & Sherwin, F.S. (1987). A uniform national data system for medical rehabilitation. In: Fuhrer, M. J., ed. Rehabilitation Outcome: Analysis and Measurement. Baltimore, Md: Paul Brookes, 137-47.
- Hamza, A.M., Nabilla, A.S., & Loh, S.Y. (2012). Evaluation of quality of life among stroke survivors: linguistic validation of the Stroke Impact Scale (SIS) 3.0 in Hausa language. Journal of Nigeria Soc Physiotherapy, 20, 52-9.
- Hamza, A.M., Nabilla, A.-S., Yim, L.S., & Chinna, K. (2014). Reliability and validity of the Nigerian (Hausa) version of the Stroke Impact Scale (SIS) 3.0 index. BioMed Research International, 14, Article ID 302097, 7 pages. doi: 10.1155/2014/302097
- Hogue, C., Studenski, S., Duncan, P.W. (1990). Assessing mobility: The first steps in preventing fall. In: Funk, SG., Tornquist, EM., Champagne, M.T., Copp, L.A., & Wiese, R.A., eds. Key Aspects of Recovery. New York, NY: Springer, 275-81.
- Hsieh, F.-H., Lee, J.-D., Chang, T.-C., Yang, S.-T., Huang, C.-H., & Wu, C.-Y. (2016). Prediction of quality of life after stroke rehabilitation. Neuropsychiatry, 6(6), 369-75.
- Huang, Y-h., Wu, C-y., Hsieh, Y-w., & Lin, K-c. (2010). Predictors of change in quality of life after distributed constraint-induced therapy in patients with chronic stroke. Neurorehabilitation and Neural Repair, 24(6), 559-66. doi: 10.1177/1545968309358074
- Jenkinson, C., Fitzpatrick, R., Crocker, H., & Peters, M. (2013). The Stroke Impact Scale: validation in a UK setting and development of a SIS short form and SIS index. Stroke, 44, 2532-5.
- Kamwesiga, J.T., von Koch, L., Kottorp, A., & Guidetti, S. (2009). Cultural adaptation and validation of Stroke Impact Scale 3.0 version in Uganda: a small-scale study. SAGE Open Medicine, 4: 2050312116671859. doi: 10.1177/2050312116671859
- Kwon, S., Duncan, P., Studenski, S., Perera, S., Lai, S.M., & Reker, D. (2006). Measuring stroke impact with SIS: Construct validity of SIS telephone administration. Quality of Life Research, 15, 367-76.
- Lai, S.M., Perera, S., Duncan, P.W., & Bode, R. (2003). Physical and Social Functioning After Stroke: Comparison of the Stroke Impact Scale and Short Form-36. Stroke, 34, 488-93.
- Lawton, M. & Brody, E. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist, 9, 179 -86.
- Lee, H.-J. & Song, J.-M. (2015). The Korean language version of Stroke Impact Scale 3.0: cross-cultural adaptation and translation. Journal of the Korean Society of Physical Medicine, 10(3), 47-55.
- Lin, K.C., Fu, T., Wu, C.Y., Hsieh, Y.W., Chen, C.L., & Lee, P.C. (2010a). Psychometric comparisons of the Stroke Impact Scale 3.0 and Stroke-Specific Quality of Life Scale. Quality of Life Research, 19(3), 435-43. doi: 10.1007/s11136-010-9597-5.
- Lin K.-C., Fu T., Wu C.Y., Wang Y.-H., Wang Y-.H., Liu J.-S., Hsieh C.-J., & Lin S.-F. (2010b). Minimal detectable change and clinically important difference of the Stroke Impact Scale in stroke patients. Neurorehabilitation and Neural Repair, 24, 486-92.
- MacIsaac, R., Ali, M., Peters, M., English, C., Rodgers, H., Jenkinson, C., Lees, K.R., Quinn, T.J., VISTA Collaboration. (2016). Derivation and validation of a modified short form of the Stroke Impact Scale. Journal of the American Heart Association, 5:e003108. doi: 10/1161/JAHA.115003108.
- Mahoney, F.I. & Barthel, D.W. (1965). Functional evaluation: The Barthel Index. Maryland State Medical Journal, 14, 61-5.
- Mulder, M. & Nijland, R. (2016). Stroke Impact Scale. Journal of Physiotherapy, 62, 117.
- Ochi, M., Ohashi, H., Hachisuka, K., & Saeki, S. (2017). The reliability and validity of the Japanese version of the Stroke Impact Scale version 3.0. Journal of UOEH, 39(3), 215-21. doi: 10.7888/juoeh.39.215
- Richardson, M., Campbell, N., Allen, L., Meyer, M., & Teasell, R. (2016). The stroke impact scale: performance as a quality of life measure in a community-based stroke rehabilitation setting. Disability and Rehabilitation, 38(14), 1425-30. doi: 10.310/09638288.2015.1102337
- Sullivan, J. (2014). Measurement characteristics and clinical utility of the Stroke Impact Scale. Archives of Physical Medicine and Rehabilitation, 95, 1799-1800.
- Vellone, E., Savini, S., Barbato, N., Carovillano, G., Caramia, M., & Alvaro, R. (2010). Quality of life in stroke survivors: first results from the reliability and validity of the Italian version of the Stroke Impact Scale 3.0. Annali di Igiene, 22, 469-79.
- Vellone, E., Savini, S., Fida, R., Dickson, V.V., Melkus, G.D., Carod-Artal, F.J., Rocco, G., & Alvaro, R. (2015). Psychometric evaluation of the Stroke Impact Scale 3.0. Journal of Cardiovascular Nursing, 30(3), 229-41. doi: 10.1097/JCN.0000000000000145
- Ward, I., Pivko, S., Brooks, G., & Parkin, K. (2011). Validity of the Stroke Rehabilitation Assessment of Movement Scale in acute rehabilitation: a comparison with the Functional Independence Measure and Stroke Impact Scale-16. Physical Medicine and Rehabilitation, 3(11), 1013-21. doi: 10.1016/j.pmrj.2011.08.537
- Ware, J.E. Jr., & Sherbourne, C.D. (1992). The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Medical Care, 30, 473-83.
- Yesavage, J.A., Brink, T., Rose, T.L., Lum, O., Huang, V., Adey, M., & Leirer, V.O. (1983). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17, 37-49.
See the measure
How to obtain the SIS?
Please click here to see a copy of the SIS.
This instrument was developed by:
- Pamela Duncan, PhD, PT
- Dennis Wallace, PhD
- Sue Min Lai, PhD, MS, MBA
- Stephanie Studenski, MD, MPH
- DallasJohnson, PhD, and
- Susan Embretson, PhD.
In order to gain permission to use the SIS and its translations, please contact MAPI Research Trust: contact@mapi-trust.org