Stroke-Adapted Sickness Impact Profile (SA-SIP30)

Purpose

The Stroke-Adapted Sickness Impact Profile (SA-SIP30 – van Straten, de Haan, Limburg, Schuling, Bossuyt, & van den Bos, 1997) was developed from the original 136-item Sickness Impact Profile (SIP-136), and assesses quality of life in patients who have sustained 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.. The scale was developed specifically for use in strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. outcome research in order to overcome the major problem observed with the SIP-136, its length (Finch, Brooks, Stratford, & Mayo, 2002).

In-Depth Review

Purpose of the measure

The Stroke-Adapted Sickness Impact Profile (SA-SIP30 – van Straten, de Haan, Limburg, Schuling, Bossuyt, & van den Bos, 1997) was developed from the original 136-item Sickness Impact Profile (SIP-136), and assesses quality of life in patients who have sustained 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.. The scale was developed specifically for use in strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. outcome research in order to overcome the major problem observed with the SIP-136, its length (Finch, Brooks, Stratford, & Mayo, 2002).

Available versions

The SA-SIP30 was adapted from the original SIP-136 first published in 1976 by Bergner, Bobbitt, Pollard, Martin, and Gilson and later revised in 1981 by Bergner, Bobbit, Carter and Gilson.

Features of the measure

Items:

van Straten et al. (1997) followed a three-stage process to eliminate items and subscales that were least relevant 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. survivors (i.e. those applying to fewer than 10% of patients) as well as those with the lowest levels of 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 .
from the original SIP (van Straten et al. 1997; Golomb, Vickrey, & Hays, 2001).

A criticism of the SA-SIP30 is that no attempt has been made to enhance the scale with items or domains of potential importance 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.. Thus, the SA-SIP30 does not assess pain, recreation, energy, general health perceptions, overall quality of life or 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. symptoms (Golomb, Vickrey, & Hays, 2001).

The SA-SIP30 contains 30 items. Each item takes the form of a statement describing changes in behavior that reflect the impact of illness on some aspect of daily life. Patients are asked to mark items most descriptive of themselves on a given day. All responses are “yes” or “no”. Scale items are weighted to reflect the relative importance of the item to health status and are the same as the weights used in the SIP-136. In addition to maintaining much of the original 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).
structure of the SIP-136, these weights help facilitate comparisons with studies using the original SIP-136.

Scoring:

The scoring of items, subscales, dimensions and total score is the same as for the original SIP. To score the scale, weights are applied to marked items, summed for each 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).
and expressed as a percentage for each 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).
ranging from 0 to 100%. Higher scores indicate less desirable health outcomes (van Straten et al., 1997; van Straten, de Haan, Limburg, & van den Bos, 2000; Finch et al., 2002; Cup, Scholte op Reimer, Thijssen, & van Kuyk-Minis, 2003). Regression weights have also been provided to allow for a calculation of estimated SIP-136 scores from SA-SIP30 scores.

Cut-off scores representative of poor health have been defined as the following: patients with scores > 33 are known to be impaired 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, unable to live independently, experience difficulties in self care, mobility and in performing their main activity. Similar profiles have been observed for Physical dimension scores > 40, but no cut-off values could be defined using the Psychosocial dimension (van Straten et al., 2000).

Subscales:

There are 8 subscales:

• Body Care and Movement (5 items)
• Social Interaction (5 items)
• Mobility (3 items)
• Communication (3 items)
• Emotional Behavior (4 items)
• Household Management (4 items)
• Alertness Behavior (3 items)
• Ambulation (3 items)

Subscales can be combined to form 2 dimensions:

• Physical: includes the subscales Body care and movement, Ambulation, Household management and Mobility (15 items)
• Psychosocial: includes the subscales Alertness behavior, Communication, Social interaction and Emotional behavior (15 items)

Equipment:

No special equipment is required to administer the SA-SIP30.

Training:

The scale is intended for self-administration or by interview (Buck, Jacoby, Massey, & Ford, 2000). No special training is necessary, however a user’s manual and trainer’s manual are available for the original SIP (McDowell & Newell, 1996). There is not yet any evidence that the SA-SIP30 can be administered by proxy, however, the original SIP-136 can be used in this fashion (Sneeuw, Aaronson, de Haan, & Limburg, 1997).

Time:

The average scale completion time has not been reported, however, the SA-SIP30 is known to be a shorter scale than the original SIP, which takes 30 minutes on average to administer.

Alternative forms of the SA-SIP30

None.

Client suitability

Can be used with:

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

Should not be used in:

• The SA-SIP30 should be administered with caution to patients who have experienced a 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.. van Straten et al. (1997) noted that the SA-SIP30 might be less effective for 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. because in developing the SA-SIP30, higher item weights were mostly associated with items that were removed, and these had been descriptive of more severe health status. Evidence of this came from the observation that agreement between scores obtained with the original SIP-136 and the SA-SIP30 were lower among more severely ill 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. than among healthier patients (van Straten et al., 1997). However, it is important to note that in a subsequent study by van de Port et al. (2004), this trend was only observed on the Physical dimension of the SA-SIP30 and even then, the trend was less notable than on the SIP-68 (a short version of the original SIP-136).
• The SA-SIP30 should be administered with caution to patients who have a major physical disability. van Straten et al. (2000) found that the total scores of the SA-SIP30 were largely explained by the Physical dimension of the scale (66% for the subscales of the Physical dimension versus 25% for the subscales of the Psychosocial dimension). This might result in any patient with a serious physical disability being automatically detected by the scale as having poor health-related quality of life.
• Patients who require a proxy to complete. Although the original SIP has been validated for proxy use, proxy use has not been examined using the SA-SIP30. For patients who have had 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. and who require a proxy, 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 is known to be a reliable and valid measure of quality of life (Duncan, Lai, Tyler, Perera, Reker, & Studenski, 2002).
• Patients with aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada). The SA-SIP30 has not been validated for use in patients with aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada). A French questionnaire, the SIP-65, has been validated to assess quality of life in patients with aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada), however this scale is not available in English (Benaim et al., 2003). 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. and AphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada) Quality of Life Scale-39 (SAQOL-39) is another measure that assesses quality of life and was developed specifically for use in patients with aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada). This scale has been found to be an acceptable, reliable, and valid measure in patients with long-term aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
  An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada) (Hilari, Byng, Lamping, & Smith, 2003).

In what languages is the measure available?

English (van Straten et al., 1997)

Summary

What does the tool measure?	Health-related quality of life
What types of clients can the tool be used for?	The SA-SIP30 was developed for use 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..
Is this a screeningTesting for disease in people without symptoms. or assessment tool?	Assessment
Time to administer	The average scale completion time has not been reported, however, the SA-SIP30 is known to be a shorter scale than the original SIP, which takes 30 minutes on average to administer.
Versions	The SA-SIP30 was adapted from the original SIP-136
Other Languages	No translations of the SA-SIP30 have been conducted to date.
Measurement Properties
ReliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .	Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.: Out of two studies that examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. internal of the SA-SIP30, both 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.. Test-retest: No studies have examined the 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 SA-SIP30. Inter-rater: No studies have examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the SA-SIP30.
ValidityThe degree to which an assessment measures what it is supposed to measure.	Content: Items least relevant 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. were eliminated. Items with a skewed response pattern or those relevant to < 10% of patients were dropped. Linear regression was used to assess the relevance of remaining items. Item selection for each 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). was completed when items in the model explained 80% of the variance in score of the original total 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). . Least relevant subscales were excluded using a stepwise linear regression with forward inclusion. When adding another 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). to the model did increase the percentage of variance more than 1%, the process was stopped. Unreliable items were excluded, as long as at least 3 items remained in each 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). . Construct: Convergent: Excellent correlations were found between the SA-SIP30 and the SIP-136 total score and subscales; the SIP-68 (shortened version of the SIP-136); and the global functional health score on the Rankin Scale. Adequate correlations with the disability score on the Barthel Index; total Rankin Scale; EuroQol; and the Frenchay ActivitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function. Index. Discriminant: 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 SA-SIP30 and the Canadian Occupational Performance Measure. Known groups: The SA-SIP30 was able to distinguish clients with lacunar infarctions from those with cortical or subcortical lesions. One study reported that when using appropriate SA-SIP30 cut-off scores, the SA-SIP30 could classify patients as dependent in their 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; patients able to live independently; and patients having poor health-related quality of life.
Floor/Ceiling Effects	None.
Does the tool detect change in patients?	One study examined found that the SA-SIP30 had only a moderate ability to detect change in patients from 6 months to 1 year post-stroke.
Acceptability	The SA-SIP30 is shorter and simpler than the original SIP-136. The original SIP has been tested for use with proxy respondents, however the SA-SIP30 has not yet been tested for use by proxy respondent. The SA-SIP30 should not be administered to patients with aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury. An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada), and should be used with caution in patients with a major physical disability or who have suffered a 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..
Feasibility	This shorter, simpler version of the SIP should represent less administrative burden and can be more easily included in both research and clinical setting. The scale is intended for self-administration or by interview. No special training is necessary. A user’s manual and trainer’s manual are available for the original SIP only. The SA-SIP30 is fairly simple to score and is based on weights that are applied to marked items, which are then summed for each 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). and expressed as a % for each 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). ranging from 0 to 100%. Higher scores indicate less desirable health outcomes.
How to obtain the tool?	Click here to find a copy of the SA-SIP30. The SA-SIP30 can also be found in van Straten et al. (1997).

Psychometric Properties

Overview

To date, only a few studies have examined the psychometric properties of the Stroke-Adapted Sickness Impact Profile (SA-SIP30). For this reason, we have included for review all of the publications that we could identify on the scale. The SA-SIP30 was originally validated by its authors (van Straten et al., 1997; van Straten et al., 2000) and was later evaluated by van der Port et al. (2004).

Reliability

Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency.:
van Straten et al. (1997) developed and examined the 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 SA-SIP30 in 319 patients post-stroke. The total SA-SIP30 demonstrated 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. (alpha = 0.85), as did the Psychosocial (alpha = 0.78) and Physical dimensions (alpha = 0.82). All subscales had 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. with the exception of the Emotional Behavior (alpha = 0.57), and Ambulation (alpha = 0.54) subscales, which were poor. With the exception of the Communication 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).
, the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the SIP-136 was found to be slightly higher on all items than the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the SA-SIP30.

van de Port, Ketelaar, Schepers, van den Bos, and Lindeman (2004) also examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the SA-SIP30 in 122 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 found excellent reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
for the total score (alpha = 0.82), and moderate reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
for the Physical dimension (alpha = 0.76). However, unlike the results of van Straten et al. (1997), the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. of the Psychosocial dimension was found to be poor (alpha = 0.68).

Inter-rater:
Not reported.

Test-retest:
Not reported.

Validity

Criterion:

None.

Content:

van Straten et al. (1997) eliminated the least relevant items 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. from the SIP-136 . Items that had a skewed response pattern were dropped, as were items relevant to less than 10% of all patients. Linear regression was used to assess the relevance of the remaining items with a forward selection strategy, using the F statistic with p = 0.5 as the criteria level for selection. The item selection for each 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).
was completed when the items in the regression model explained 80% of the variance in score of the original total 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).
. The least relevant subscales were excluded by applying a stepwise linear regression with forward inclusion to explain the variation of the original total SIP score with the shortened subscales. When adding another 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).
to the model did not result in an increase in the percentage of variance more than 1%, the process was stopped. Finally, unreliable items were excluded, while ensuring that at least three items remained in each 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).
.

Construct:

A principal component analysis supported two dimensions (Physical and Psychosocial), which is evidence that the original dimension structure of the SIP-136 was retained with the SA-SIP30 (van Straten et al., 1997). Twenty percent of the SA-SIP30-explained score variance could be attributed to the Physical dimension and 11% to the Psychosocial dimension (van Straten et al., 1997).

Convergent:
van Straten et al. (1997) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the scale by comparing the scores of the SA-SIP30 with the scores on the 136-item version in 319 patients post-stroke. The SA-SIP30 total score explained 91% of the variance in SIP-136 scores. Furthermore, 87% of the original Physical dimension scores and 88% of the Psychosocial dimension scores could be explained by the SA-SIP30. For the different subscales, the percentages of explained variance ranged from 69% (Social Interaction) to 84% (Emotional Behavior). The Spearman rank correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient between the SA-SIP30 and the SIP-136 total scores was excellent (r = 0.96). 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).
correlations were also excellent, ranging from r = 0.75 (Emotional Behavior) to r = 0.90 (Body Care and Movement).

Also in this study by van Straten et al., the SA-SIP30 was correlated with the Barthel Index and the Rankin Scale. As expected, SA-SIP30 correlated moderately with the disability score on the Barthel Index (r = 0.50) and had 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 global functional health score on the Rankin Scale (r = 0.68), further demonstrating the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the SA-SIP30.

van de Port, Ketelaar, Schepers, van den Bos, and Lindeman (2004) examined the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the SA-SIP30 in 122 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 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 SA-SIP30 and total SIP-68 (a shortened version of the SIP-136) scores was excellent (r = 0.98). Similar associations were reported for the Physical (r = 0.89) and Psychosocial (r = 0.84) dimension scores.

Cup et al. (2003) found that the SA-SIP30 correlated adequately with the Barthel Index (r = -0.517), the Rankin Scale (r = 0.468), the EuroQol (r = -0.483), and the Frenchay ActivitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
Index (r = -0.426). The correlations among the SA-SIP30 and the EuroQol, Barthel Index, and Frenchay ActivitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
Index are negative because a high score on the SA-SIP30 indicates poor health outcomes, whereas a high score on these other scales indicates positive health outcomes. The results of this study demonstrate the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the SA-SIP30 with other frequently used standardized functional measures in strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..

van Straten et al. (2000) conducted a linear regression analysis and found that common measures of physical disability were closely associated with SA-SIP30 scores. The Barthel Index accounted for 36% of the variance in total SA-SIP30 scores, the Rankin scale accounted for 53%, and the Euroqol index score accounted for 44%. The results of this study also confirm the convergent validityA type of validity that is determined by hypothesizing and examining the overlap between two or more tests that presumably measure the same construct. In other words, convergent validity is used to evaluate the degree to which two or more measures that theoretically should be related to each other are, in fact, observed to be related to each other.
of the SA-SIP30 with other frequently used standardized functional measures in strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..

Discriminant.
Cup et al. (2003) examined the 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 Canadian Occupational Performance Measure in 26 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.. As predicted, 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 scores on the Canadian Occupational Performance Measure and the SA-SIP30 was poor (r = 0.102). This was to be expected because the Canadian Occupational Performance Measure was developed to examine issues specific to the individual, whereas the SA-SIP30 is focused on a societal perspective of independence.

Known groups:
van Straten et al. (1997) found that the SA-SIP30 was unable to distinguish between clients with supratentorial and infratentorial strokes, as has been possible with the SIP-136 (de Haan, Limburg, & van der Meulen, 1995). However, the SA-SIP30 was able to distinguish clients with lacunar infarctions from those with cortical or subcortical lesions. Further, clients with lacunar infarcts reported better functional health than those with cortical or subcortial lesions on the Psychosocial dimension of the scale, the total SA-SIP30 score, and on all subscales with the exception of Emotional Behavior and Mobility.

van Straten et al. (2000) identified the cut-off scores for poor health outcomes by examining the area under the ROC curves (AUC). When using a cut-off SA-SIP30 score > 28, the percentage of patients correctly classified as dependent in their 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 on the SA-SIP30 as assessed using the Barthel Index was adequate, 77% (AUC = 0.84). When using a cut-off SA-SIP30 score > 40 for the Physical dimension alone, the percentage of patients correctly classified as dependent in their 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 was excellent, 84% (AUC = 0.90). When using a cut-off SA-SIP30 score > 25, the percentage of patients correctly classified as unable to live independently by the SA-SIP30 as measured by the Rankin Scale was adequate for the total score was excellent, 80% (AUC = 0.90). When using a cut-off of > 36 for the Physical dimension alone, the percentage of patients correctly classified was excellent, 83% (AUC = 0.90). When using a cut-off of > 33, the percentage of patients correctly classified as having poor health-related quality of life as assessed by the EuroQol was adequate, 80% (AUC = 0.80) for the total score. When using a cut-off > 40 for the Physical dimension alone, the percentage of patients correctly classified was also adequate, 79% (AUC = 0.86).

Responsiveness

van de Port et al. (2004) found that the SA-SIP30 demonstrated moderate responsivenessThe ability of an instrument to detect clinically important change over time.
in a longitudinal study. Effect sizes from 6 months to 1 year post-stroke were 0.60 for the total SA-SIP30 scores, and 0.56 and 0.65 for the Physical and Psychosocial dimensions, respectively.

References

• Benaim, C., Pelissier, J., Petiot, S., Bareil, M., Ferrat, E., Royer, E., Milhau, D., Herisson, C. (2003). A French questionnaire to assess quality of life of the aphasic patient: The SIP-65. [French]. Ann Readapt Med Phys, 46(1), 2-11.

• Bergner, M., Bobbitt, R. A., Pollard, W. E., Martin, D. P., Gilson, B. S. (1976). The sickness impact profile: Validation of a health status measure. Med Care, 14(1), 57-67. 

• Bergner, M., Bobbit, R. A., Carter, W. B., Gilson, B. S. (1981). The Sickness Impact Profile: development and final revision of health status measure. Med Care, 19, 787-805.

• Buck, D., Jacoby, A., Massey, A., Ford, G. (2000). Evaluation of measures used to assess quality of life after stroke. Stroke, 31, 2004-2010.

• Coons, S. J., Rao, S., Keininger, D. L., Hays, R. D. (2000). A comparative review of generic quality-of-life instruments. Pharmacoeconomics, 17, 13-35.

• Cup, E. H. C., Scholte op Reimer, W. J. M., Thijssen, M. C., E., van Kuyk-Minis, M. A. H. (2003). Reliability and validity of the Canadian Occupational Performance Measure in stroke patients. Clinical Rehabilitaton, 17(4), 402-409.

• de Haan, R. J., Limburg, M., van der Meulen, J. H. P. (1995). Quality of life after stroke. Stroke, 26, 402-408.

• Duncan, P. W., Lai, S. M., Tyler, D., Perera, S., Reker, D. M., Studenski, S. (2002). Evaluation of proxy responses to the Stroke Impact Scale. Stroke, 33, 2593-2599.

• Finch, E., Brooks, D., Stratford, P. W., Mayo, N. E. (2002). Physical Rehabilitations Outcome Measures. A Guide to Enhanced Clinical Decision-Making (second ed.), Canadian Physiotherapy Association, Toronto.

• Golomb, B. A., Vickrey, B. G., Hays, R. D. (2001). A review of health-related quality-of-life measures in stroke. Pharmacoeconomics, 19(2), 155-185.

• Hilari, K., Byng, S., Lamping, D. L., Smith, S. C. (2003). Stroke and Aphasia Quality of Life Scale-39 (SAQOL-39): Evaluation of acceptability, reliability, and validity. Stroke, 34, 1944-1950.

• Lurie, J. (2000). A review of generic health status measures in patients with low back pain. Spine, 25, 3125-3129.

• McDowell, I., Newell, C. (1996). Measuring Health. A Guide to Rating Scales and Questionnaires (2nd ed.), New York: Oxford University Press.

• Sneeuw, K. C. A., Aaronson, N. K., de Haan, R. J., Limburg, M. (1997). Assessing quality of life after stroke. The value and limitations of proxy ratings. Stroke, 28, 1541-1549.

• van Straten, A., de Haan, R. J., Limburg, M., Schuling, J., Bossuyt, P. M., van den Bos, G. A. M. (1997). A Stroke-Adapted 30-Item Version of the Sickness Impact Profile to Assess Quality of Life (SA-SIP30). Stroke, 28, 2155-2161.

• van Straten, A., de Haan, R. J., Limburg, M., van den Bos, G. A. M. (2000). Clinical Meaning of the Stroke-Adapted Sickness Impact Profile-30 and the Sickness Impact Profile-136. Stroke, 31, 2610-2615.

• van de Port, I. G. L., Ketelaar, M., Schepers, V. P. M., van den Bos, G. A. M., Lindeman, E. (2004). Monitoring the functional health status of stroke patients: the value of the Stroke-Adapted Sickness Impact Profile-30. Disability and Rehabilitation, 26(11), 635-640.

See the measure

How to obtain a copy of the SA-SIP30?

The measure is provided in van Straten et al. (1997). Please click to view a copy of the SASIP-30.