Functional Independence Measure (FIM)

Purpose

The Functional Independence Measure (FIM) was developed to address the issues 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.”
and comprehensiveness that were criticized as being problematic with the Barthel Index (another measure of functional independence). The FIM was also developed to offer a uniform system of measurement for disability based on the International Classification of Impairment, Disabilities and Handicaps for use in the medical system in the United States (McDowell & Newell, 1996). The level of a patient’s disability indicates the burden of caring for them and items are scored on the basis of how much assistance is required for the individual to carry out 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.

In-Depth Review

Purpose of the measure

The Functional Independence Measure (FIM) was developed to address the issues 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."
and comprehensiveness that were criticized as being problematic with the Barthel Index (another measure of functional independence). The FIM was also developed to offer a uniform system of measurement for disability based on the International Classification of Impairment, Disabilities and Handicaps for use in the medical system in the United States (McDowell & Newell, 1996). The level of a patient’s disability indicates the burden of caring for them and items are scored on the basis of how much assistance is required for the individual to carry out 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.

The FIM assesses six areas of function (Self-care, Sphincter control, Transfers, Locomotion, Communication and Social cognition), which fall under two Domains (Motor and Cognitive). It has been tested 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., traumatic brain injury, spinal cord injury, multiple sclerosis, and elderly individuals undergoing inpatient rehabilitation and has been used with children as young as 7 years old.

Available versions

The FIM was developed between 1984 and 1987 by a national task force sponsored by the American Academy of Physical Medicine and Rehabilitation and the American Congress of Rehabilitation Medicine and was published by Keith, Granger, Hamilton, and Sherwin in 1987.

Features of the measure

Items:

The FIM consists of 18 items assessing 6 areas of function. The items fall into two domains: Motor (13 items) and Cognitive (5 items). The motor items are based on the items of the Barthel Index. These domains are referred to as the Motor-FIM and the Cognitive-FIM.

The items of the FIM are listed as follows:

Motor Domain:

1. Self-care (6 items)

– Eating
– Grooming
– Bathing
– Dressing – Upper body
– Dressing – Lower body
– Toileting

2. Sphincter control (2 items)

– Bladder management
– Bowel management

3. Transfers (3 items)

– Bed/Chair/Wheelchair
– Toilet
– Tub/Shower

4. Locomotion (2 items)

– Walk/Wheelchair
– Stairs

Cognitive Domain:

5. Communication (2 items)

– Comprehension
– Expression

6. Social cognition (3 items)

– Social interaction
– Problem solving
– Memory

For the Motor-FIM, the Eating, Grooming, and Bowel management items are known to be the easiest 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. to accomplish, whereas Tub/Shower transfers and Locomotion (Walk/Wheelchair, Stairs) are the most challenging items (Granger, Cotter, Hamilton, & Fiedler, 1993; Grimby, Gudjonsson, Rodhe, Sunnerhagen, Sundh, & Ostensson, 1996). For the Cognitive-FIM, performance of the Expression item has been found to be the easiest for patients to accomplish, and Problem solving has been found to be the most challenging (Granger et al., 1993).

Time:

The FIM is reported to take between 30-45 minutes to administer and score, with 7 minutes to gather demographic information.

Scoring:

Each item on the FIM is scored on a 7-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., and the score indicates the amount of assistance required to perform each item (1 = total assistance in all areas, 7 = total independence in all areas). The ratings are based on performance rather than capacity and can be acquired by observation, patient interview, telephone interview or medical records. The developers of the FIM recommend that the scoring be derived by consensus with a multi-disciplinary team.

A final summed score is created and ranges from 18 – 126, where 18 represents complete dependence/total assistance and 126 represents complete independence. The single summed raw score may be misleading as it gives the appearance of a continuous scale. However, intervals between scores are not equal in terms of level of difficulty and cannot provide more than ordinal level information (Linacre et al., 1994). Kidd et al. (1995) suggested using the summed scores as though on an interval scale while the individual items remain ordinal. Granger, Deutsch, and Linn (1998) have applied a Rasch rating scale in order to transform the FIM’s ordinal ratings to an equal-interval rating scale so that it can be used for linear regression models.

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 for the Motor and Cognitive domains can also be calculated (Linacre, Heinemann, Wright, Granger, & Hamilton, 1994).

Equipment:

Any items that the patient uses to carry out 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.

Subscales:

There are two subscales for the FIM: the Motor-FIM and the Cognitive-FIM.

Training:

The FIM must be administered by a trained and certified evaluator.

Grey and Kennedy (1993) found that the FIM could be completed as a self-report questionnaire in patients with spinal cord injury. Segal and Schall (1994) found that the FIM can be used reliably by in-person proxy 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.. Segal, Gillard, and Schall (1996) further established that the FIM can be used reliably by proxy over the telephone 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. (total FIM, intraclass correlation coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance. = 0.91, Motor-FIM, ICC = 0.94; Cognitive-FIM, ICC = 0.52), and closely resembles results obtained for the in-person administration.

Alternative Forms of the Functional Independence Measure

• The Functional Independence Measure for Children (WeeFIM). This measure was developed to track disability in children who are between the ages of 6 months and 7 years. The WeeFIM can be administered to children over the age of 7 if their functional abilities are below those expected of children aged 7 who do not have disabilities. It measures the impact of developmental strengths and difficulties on independence at home, in school, and in the community (Msall et al., 1994). The scale has 18 items measuring functional performance in 3 domains: Self-care, Mobility, and Cognition (Uniform Data System for Medical Rehabilitation, http://www.udsmr.org/).
• Modified 5-level FIM. Gosman-Hedström and Blomstrand (2004) examined whether a 5-level FIM would be more useful than the standard 7-level version in large population studies. They used a sample of elderly 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 and found that a 5-level FIM would most likely increase 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 FIM without losing 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.”
  .

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. of all ages, and can be used with patients with special conditions (e.g. 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) or neglect).

Should not be used in:

No restrictions have been reported.

In what languages is the measure available?

The FIM has been translated in the following languages:

• German
• Italian
• Spanish
• Swedish
• Finnish
• Portuguese
• Afrikaans
• Turkish
• French
• Persian (Farsi)

Summary

What does the tool measure?	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
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., traumatic brain injury, spinal cord injury, multiple sclerosis, and elderly individuals undergoing inpatient rehabilitation. Can be used with children as young as 7 years old.
Is this a screeningTesting for disease in people without symptoms. or assessment tool?	Assessment
Time to administer	The FIM is reported to take between 30-45 minutes to administer and score, with 7 minutes to gather demographic information.
Versions	WEE-FIM; Modified 5-level FIM
Other Languages	German; Italian; Spanish; Swedish; Finnish; Portuguese; Afrikaans; Turkish; French; Persian (Farsi).
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 four studies examining 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., all four 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: Out of five studies examining 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). , all five reported excellent test-retest. Inter-rater: Out of 10 studies examining 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. , eight studies reported excellent; one reported adequate to excellent (except Social Interaction item which was poor); one reported overall poor kappa values, but excellent intraclass correlation coefficient (ICC)Intraclass correlation (ICC) is used to measure inter-rater reliability for two or more raters. It may also be used to assess test-retest reliability. ICC may be conceptualized as the ratio of between-groups variance to total variance..
ValidityThe degree to which an assessment measures what it is supposed to measure.	Content: The FIM was created based on the results of a literature review of published and unpublished measures and expert panels and was then piloted in 11 centers. The Delphi method was applied, using rehabilitation expert opinion to establish the inclusiveness and appropriateness of the items. Criterion: Excellent correlations with the Barthel Index; Modified Rankin Scale; Disability Rating Scale. FIM scores found to predict amount of home care required; admission scores predict FIM discharge scores; placement after discharge; functional gain; length of stay; 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. , ability to return to work 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. or traumatic brain injury. Concurrent: The Motor-FIM was found to demonstrate 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 Modified Rankin Scale (MRS) and the Disability Rating Scale (DRS); and 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. with the Barthel Index. The Cognition-FIM was found to have 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 DRS; 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 Montebello Rehabilitation Factor Score (MRFS) (efficacy); 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. with the MRFS (efficiency). Construct: FIM scores discriminated between groups based on spinal cord injury and strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. severity, and the presence of comorbid illness both at admission and discharge. It has also been found to distinguish between patients with or without neglect and with or without 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) at both admission and discharge. Convergent/Discriminant: The total FIM was found to demonstrate 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 Office of Population Censuses and Surveys Disability Scales disability scores; 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 London Handicap Scale and the Wechsler Adult Intelligence Test-verbal IQ test; 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. with the SF-36 Physical and Mental components, and the General Health Questionnaire. The Motor-FIM was found to demonstrate 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 Office of Population Censuses and Surveys Disability Scales disability scores; 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 London Handicap 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. with the Wechsler Adult Intelligence Test-verbal IQ test, SF-36 Physical and Mental components, and the General Health Questionnaire. The Cogntion-FIM was found to demonstrate 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 Mini-Mental State Examination (MMSE); 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 Lowenstein Occupational Therapy Cognitive Assessment (LOTCA), Office of Population Censuses and Surveys Disability scores, and the revised Wechsler Adult Intelligence Test-verbal IQ; 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. with the London Handicap Scale, SF-36 Physical and Mental components, and the General Health Questionnaire. Ecological: The Motor-FIM demonstrated poor correlations with the Occupational Therapy Adult Perceptual ScreeningTesting for disease in people without symptoms. Test (OT-APST). The Cognition-FIM demonstrated adequate correlations with the OT-APST.
Does the tool detect change in patients?	A significant 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.” has been detected with the Cognitive domain of the FIM. Out of seven studies examined, three reported that the FIM has an excellent ability to detect change 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., four reported poor ability to detect change 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. or multiple sclerosis.
Acceptability	The FIM is typically administered by interview. 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., it can be 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 . administered to proxy respondents.
Feasibility	Training and education of persons to administer the FIM may represent significant cost. Use of interview formats may make the FIM more feasible for longitudinal assessment.
How to obtain the tool?	Click here to find a copy of the FIM (the original comes from the following website: http://www.va.gov/vdl/documents/Clinical/Func_Indep_Meas/fim_user_manual.pdf) http://www.udsmr.org

Psychometric Properties

Overview

We conducted a literature search to identify all relevant publications on the psychometric properties of the FIM.

Floor/Ceiling Effects

Van der Putten, Hobart, Freeman and Thompson (1999) compared the Motor-FIM and total FIM to the Barthel Index in 201 patients with multiple sclerosis and 82 post-stroke patients undergoing inpatient neurorehabilitation. The Cognitive-FIM had poor ceiling effects in patients with multiple sclerosis (36%) and adequate ceiling effects 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.. The total FIM showed no 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." (0%) in both 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 patients with multiple sclerosis, as compared to 7% for the Barthel Index (1% for the Motor-FIM).

Hsueh, Lin, Jeng, and Hsieh (2002) compared the Motor-FIM, the original 10-item Barthel Index, and the 5-item short form Barthel Index in inpatients 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. receiving rehabilitation. They reported a substantially larger 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."
for admission Barthel Index scores than for admission Motor-FIM scores (18.2% vs. 5.8% respectively).

Hobart and Thompson (2001) compared the modified Barthel Index, the FIM and the 30-item FIM plus Functional Assessment Measure (FIM + FAM) in 149 patients with various neurological disorders. No significant floor or ceiling effects were reported in this study for the total FIM, although there was a 16.1% 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." noted for the Cognitive-FIM.

Brock, Goldie, and Greenwood (2002) examined the ceiling effects of the Motor-FIM and the Motor Assessment Scale in 106 rehabilitation inpatients 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 discharge. The ceiling effects for the Motor-FIM were adequate (16%), and 29% of the patients achieved the highest score on the hardest item of the Motor-FIM. In comparison, the Motor Assessment Scale had 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." of 25% (poor) and 35% of patients scored the highest score on the most difficult item.

Dromerick, Edwards, and Diringer (2003) assessed 95 consecutive admissions to a stroke rehabilitation service for disability on admission and discharge. No floor or ceiling effects were reported at admission to or discharge from rehabilitation with the FIM, whereas the Barthel Index demonstrated a large 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." at discharge (27%).

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.:
Dodds, Martin, Stolov and Deyo (1993) examined the psychometric properties of the FIM by analyzing Uniform Data System data on 11,102 general rehabilitation inpatients. Common diagnoses were 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. (52%), orthopedic conditions (10%), and brain injury (10%). The FIM demonstrated an 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., with a Cronbach’s alpha of 0.93 for overall admissions and 0.95 for discharges.

Hsueh, Lin, Jeng, and Hsieh (2002) 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 FIM in 118 inpatients 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.. Patients were administered the Motor-FIM 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).
at admission to a rehabilitation ward of a hospital and before discharge from the hospital. The Motor-FIM 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., with an alpha = 0.88 at admission and an alpha = 0.91 at discharge.

Hobart et al. (2001) 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 FIM, the Barthel Index and the FIM plus Functional Assessment Measure in 149 rehabilitation inpatients with neurologic disorders. Item-to-total correlations were adequate and ranged from 0.53 to 0.87 for the FIM total, 0.60 for the Motor-FIM and 0.63 for the Cognitive-FIM. Mean inter-item correlations were also adequate, and were reported as 0.51 for the total FIM, 0.56 to 0.91 for the Motor-FIM and 0.72 to 0.80 for the Cognitive-FIM. Cronbach alpha levels were excellent for the total FIM (alpha = 0.95), the Motor-FIM (alpha = 0.95), and for the Cognitive-FIM (alpha = 0.89). The results of this study demonstrate 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 total FIM and its Motor and Cognitive domains.

Sharrack, Hughes, Soudain, and Dunn (1999) assessed 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 FIM in patients with multiple sclerosis. 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 FIM was excellent, with a Cronbach’s alpha of 0.98.

Test-retest:
Chau, Daler, Andre and Patris (1994) 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 FIM in 254 patients under 20 years old in a rehabilitation centre. 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).
was found to be excellent (ICC = 0.93 for total FIM).

Segal, Ditunno, and Staas (1993) 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 FIM at discharge from an acute care rehabilitation setting and again at admission to an ongoing rehabilitation setting in 57 patients with spinal cord injuries. The two ratings were performed within 6 days of each other. The total FIM demonstrated excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
(r = 0.83).

Kidd et al. (1995) compared the FIM to the Barthel Index in two groups of 25 patients undergoing neurorehabilitation. Test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
was found to be excellent for the FIM (r = 0.90).

Ottenbacher, Hsu, Granger, and Fiedler (1996) 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 FIM by examining the results of 11 studies including a total of 1,568 patients. The median test-retest was excellent (r = 0.95).

Pollak, Rheault, and Stoecker (1996) assessed 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 FIM in 49 individuals over the age of 80 years. Individuals were tested twice using the FIM. Excellent test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
was found for the Motor-FIM (ICC = 0.90), and for the Cognitive-FIM (ICC = 0.80).

Intra-rater:
Sharrack, Hughes, Soudain, and Dunn (1999) assessed the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the FIM (using both kappa and ICC statistics) in 35 patients with multiple sclerosis. Three raters followed patients for 9 months, with assessments every 3 months. The kappa value for the total FIM was poor (kappa = 0.28), however the ICC was excellent (ICC = 0.94). For individual items, kappa coefficients ranged from adequate (kappa = 0.55 for Dressing-lower body) to excellent (kappa = 1.00 for both Expression and Social interaction). ICC’s for individual items ranged from adequate (kappa = 0.60 for Bladder control) to excellent (ICC = 1.00 for both Expression and Social interaction).

Hobart et al. (2001) examined the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
of the FIM, the Barthel Index and the FIM plus Functional Assessment Measure in 56 rehabilitation inpatients with neurologic disorders. Patients were examined by the same multidisciplinary team on two occasions. Intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
was calculated using ICC statistics. The total FIM, Motor-FIM and Cognitive-FIM were all found to have excellent intra-rater reliabilities (ICC = 0.98, 0.98 and 0.95, respectively).

Inter-rater:
Chau, Daler, Andre and Patris (1994) 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 FIM between educators, occupational therapists and physiotherapists in 254 patients under 20 years old in a rehabilitation centre. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the total FIM was excellent (ICC = 0.94).

Ottenbacher, Mann, Granger, Tomita, Hurren, and Charvat (1994) 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 FIM and the 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 Scale in 20 community-dwelling older patients. Two raters administered the tests over a short (7-10 days) or long (4-6 week) interval. The ICCs for inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
were excellent, ranging from 0.90 to 0.99.

Ottenbacher, Hsu, Granger, and Fiedler (1996) 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 FIM by examining the results of 11 studies including a total of 1,568 patients. The median inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the total FIM was excellent (r = 0.95).

Hamilton, Laughlin, Fiedler and Granger (1994) 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 FIM in 1,018 patients. The total FIM ICC was excellent (ICC = 0.96), as was the Motor-FIM domain (ICC = 0.96), and the Cognitive-FIM domain (ICC = 0.91).

Jaworski, Kult, and Boynton (1994) compared 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 observed and reported FIM ratings. In this study, 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 FIM was found to be excellent (ICC = 0.99).

Kidd et al. (1995) compared the FIM to the Barthel Index in two groups of 25 patients undergoing neurorehabilitation. 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.
was found to be excellent for the FIM (r = 0.92).

Segal and Schall (1994) 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 FIM in 38 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 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 measure was found to be excellent, with an ICC of 0.96.

Brosseau and Wolfson (1994) 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 FIM in patients with multiple sclerosis and found that the FIM has an excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(ICC = 0.83).

Daving, Andren, Nordholm, and Grimby (2001) 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 FIM in 63 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., approximately 2 years after strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. onset. Two raters (between three occupational therapists and one nurseIn charge of, but not limited to, the "assessment and provision of care needs; support and education for patients and families; discharge planning."(Suggested by Philips et al, 2002)
) conducted independent ratings of the FIM in the patient’s home, and the interview procedure was repeated within a week by another two raters in the clinic. The kappa values during the same interview exceeded 0.40 for 17 items, demonstrating adequate to excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
, however, the Social interaction item kappa value was poor (kappa = 0.26). In comparing the two interviews, kappa values were between 0.40-0.60 for Self-care items (except Bathing) and Sphincter control (except Bowel management), however, most of the Transfers, Locomotion and Social cogniton items had kappa values below 0.40. The two interviews were also studied using ICC statistics between all raters. ICC’s ranged from adequate (0.62 for Bowel management) to excellent (0.88 for Bathing) for the 13 motor items, and were adequate (ranging from 0.60 to 0.72) for the Cognitive domain, except for the Social interaction item which had an ICC of only 0.44. Significant differences were found between raters on the Wilcoxon testThe Wilcoxon test is a nonparametric test that compares two paired groups. This test calculates and then analyzes the differences between the pairs. The Wilcoxon Rank Sum test is used to determine whether two scores have the same continuous distribution. The Wilcoxon Signed Rank test is suitable to use as an alternative to the paired t-test when the scores are not normally distributed.
for the Dressing, Transfer Toilet, Transfer Tub/Shower, Walk/Wheelchair and the Cognitive domain. The results of this study show that the FIM demonstrates high 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.
in the same interview setting (whether at home or at the clinic), however the stability over time with a repeated interview by different raters is less reliable.

Sharrack, Hughes, Soudain, and Dunn (1999) assessed 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 FIM (using both kappa and ICC statistics) in 64 patients with multiple sclerosis. Each patient was assessed by three raters (2 neurologists, 1 neurology research nurseIn charge of, but not limited to, the "assessment and provision of care needs; support and education for patients and families; discharge planning."(Suggested by Philips et al, 2002)
). The kappa value for the total FIM score was poor (kappa = 0.21), however the ICC was excellent (ICC = 0.99). For individual items, kappa coefficients were variable and ranged from poor (kappa = 0.26 for Comprehension) to excellent (kappa = 0.88 for Stairs locomotion). ICC’s for the individual items were excellent, ranging from 0.76 to 0.99 with the exception of the Comprehension item, which demonstrated adequate inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(ICC = 0.56).

Validity

Content:

The FIM was created based on the results of a literature review of published and unpublished measures and expert panels. To establish content and 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.
, the FIM was then piloted in 11 centers (including 114 clinicians from 8 different disciplines and 110 patients evaluated) (Keith & Granger, 1987). Face and content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
were both determined by applying the Delphi method, using rehabilitation expert opinion to establish the inclusiveness and appropriateness of the items (Granger, Hamilton, Keith, Zielezny, & Sherwins, 1986).

Criterion:

Concurrent:
Hsueh, Lin, Jeng, and Hsieh (2002) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the Motor-FIM by examining its interrelations with the original 10-item Barthel Index, and the 5-item short form Barthel Index in 118 inpatients 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. receiving rehabilitation. 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 ICC and Spearman correlations. The Motor-FIM exhibited excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
at admission as measured by 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.
(r = 0.74) and adequate validityThe degree to which an assessment measures what it is supposed to measure.
as measured by ICC (ICC = 0.55). The Motor-FIM exhibited excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
at discharge (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.
= 0.92, ICC = 0.86).

Kwon, Hartzema, Duncan and Min-Lai (2004) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the Barthel Index, the FIM and the Modified Rankin Scale in a sample of post-stroke patients. 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 were excellent between the Barthel Index and the Motor-FIM (r = 0.95) and between the Motor-FIM and the Modified Rankin Scale (r = -0.89).
Note: This 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.
is negative because a high score on the FIM indicates functional independence, whereas a high score on the Modified Rankin Scale indicates severe disability).

Hall, Hamilton, Gordon, and Zasler (1993) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the Disability Rating Scale, the FIM, and the Functional Assessment Measure. Excellent correlations were found between the Motor-FIM and Cognition-FIM and the Disability Rating Scale (r = 0.64 and 0.73, respectively).

Zwecker et al. (2002) examined the relationship between cognitive status and functional motor outcomes in 66 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.. Functional motor outcomes were measured from efficacy and efficiency of the FIM motor scores (isolated from total FIM scores) and the Montebello Rehabilitation Factor Score (MRFS). Using Pearson’s correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
, 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.
was found between the FIM cognitive subtest and MRFS efficacy (r=0.34, p<0.01). 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.
was found between the FIM cognitive and MRFS efficiency (r=0.28, p<0.05). No significant correlations were found between the FIM cognitive and FIM motor efficacy or efficiency scores.

Predictive:
For an extensive review of 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 FIM, please see:

Timbeck, R. J., Spaulding, S. J. (2003). Ability of the Functional Independence Measure to predict rehabilitation outcomes 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.: A review of the literature. Physical & Occupational Therapy in Geriatrics, 22(1), 63-76.

Chumney, D., Nollinger, K., Shesko, K., Skop, K., Spencer, M., Newton, R.A. (2010). Ability of Functional Independent Measure to accurately predict functional outcome of stroke-specific population: Systematic reviewA systematic review is a summary of available research on a given topic that compares studies based on design and methods. It summarizes the findings of each, and points out flaws or potentially confounding variables that may have been overlooked. A critical analysis of each study is done in an effort to rate the value of its stated conclusions. The research findings are then summarized, and a conclusion is provided.
. Journal of Rehabilitation and Development, 47, 17-30.

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 FIM in the amount of care patients require in their homes:
Granger, Cotter, Hamilton, Fiedler, and Hens (1990) examined whether the FIM could predict the amount of help (measured in minutes of assistance provided per day by another person in the home) patients with multiple sclerosis required, using a bivariate regression analysis. Burden of care was assessed as help in minutes per day. It was found that a 1-point improvement in total FIM score predicted a 3.38-minutes reduction in help from another person per day. The FIM was found to be more predictive than the Barthel Index, the Incapacity Status Scale, and the Environmental Status Scale. The FIM was also found to contribute to the prediction of patient general life satisfaction.

Granger, Cotter, Hamilton and Fiedler (1993) examined whether the FIM could predict the physical care needs (measured in minutes of assistance provided per day by another person in the home) of patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain.. Burden of care was assessed as help in minutes per day. It was found that a 1-point improvement in total FIM score predicted a 2.19-minute reduction in help from another person per day. The FIM, along with the Brief Symptom Inventory, was found to contribute to the prediction of patient general life satisfaction.

Corrigan, Smith-Knapp and Granger (1997) 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 FIM for patients with traumatic brain injury after discharge from acute rehabilitation. They found that the Motor-FIM predicted which patients required direct assistance with 83% accuracy, the Cognitive-FIM predicted which patients required supervision with 77% accuracy, and the Motor-FIM and Cognitive-FIM predicted which patients required any assistance with 78% accuracy. Further, the Motor-FIM score alone was the best predictor of the number of minutes of assistance needed.

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 FIM with discharge FIM scores, discharge destinations, length of stay, functional gain, 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.
, survival, and the ability to return to work 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. or traumatic brain injury:
Inouye et al. (2000) performed a multivariate analysis on data from rehabilitation 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. obtained from patient medical records to identify predictors of functional outcome using total FIM scores. It was found that total FIM admission scores was the strongest predictor of total FIM discharge scores. No relationship was found between total FIM scores at discharge and gender, hospital length of stay, or the nature of the strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain..

Oczkowski and Barreca (1993) examined whether the FIM could predict prognosis in 113 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. observed from admission to discharge. It was found that the admission FIM score was predictive of placement after discharge and of outcome disability. No patients with an admission FIM score below 36 were discharged home, while all of the patients with admission FIM scores above 96 were discharged home. However, discharge destination became difficult to predict in patients with a moderate range of disability (i.e. an FIM score > 36 or < 97). When individual FIM items were considered, a patient’s level of independence with bowel and bladder management was predictive of functional outcome and discharge destination.

Alexander (1994) 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 FIM in a sample of 520 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. admitted to a rehabilitation hospital. It was found that an admission FIM score of < 40 resulted in an acute care stay almost twice as long as any other FIM score. Patients aged < 55 years all were discharged home regardless of their initial severity. Patients with an FIM score < 40 and who were > 55 years old had a 50% chance of being discharged to a long term care facility. This is in contrast to the findings by Oczkowski and Barreca (1993) who found that no patients with an admission FIM score < 36 were discharged to home. Patients with an admission FIM score between 40-60 who were > 74 years were at high risk for discharge to a long term care facility. Patients with an FIM score > 80 were discharged home.

Mokler, Sandstrom, Griffin, Farris, and Jones (2000) found that in the acute care phase of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. recovery, the FIM scores for Eating, Bathing, Dressing – Lower body, Toileting, Bowel management and Social interaction and predicted discharge destination with 70% accuracy. In the later phase of recovery in rehabilitation, particularly in patients with 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., scores on admission FIM items including Bladder management, Toilet transfer, and Memory, and scores on the discharge FIM items including Dressing – Upper body, Bed/Chair/Wheelchair transfers and Comprehension were associated with predicting discharge destination with up to 75% accuracy. These three admission items and three discharge items correctly predicted discharge placement in 2/3 and 3/4 of the cases, respectively.

Black, Soltis, and Bartlett (1999) examined the FIM scores of 234 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. admitted to a rehabilitation facility over a 2-year period. Patients who were discharged home were less likely to have a caregiver who worked (20%) versus patients who were discharged to long-term care (65%). The availability of a non-working family member to provide assistance and supervision was a critical factor related to discharge home. Patients with a discharge FIM score > 80 had a high probability of being discharged home when social factors (e.g. availability of family support and non-working family member) were taken into consideration. Thus, both functional status and social factors, such as family availability and support, are critical elements in predicting the discharge destination of this patient population.

Ring et al. (1997) examined 151 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. admitted to a rehabilitation centre over a 2-year period. They found that admission FIM scores and length of stay were the most significant predictors of functional gain.

Heinemann, Linacre, Wright, Hamilton, and Granger (1994) examined the extent to which functional outcome measures could predict functional status in patients with traumatic brain injury. They report that admission FIM scores were related to discharge function and length of stay. Admission Motor-FIM scores were found to be a stronger predictor of length of stay than Cognitive-FIM scores and accounted for 52% of the variance in discharge motor function. Admission Cognitive-FIM scores accounted for 46% of the variance in discharge cognitive function.

Ween, Mernoff, and Alexander (2000) 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 FIM in 244 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 an acute rehabilitation centre. It was found that patients with an admission FIM score < 50 were dependent in their self-care 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.
upon discharge. Patients who scored < 70, nine days post-stroke, were highly likely to remain functionally dependent at discharge. Patients who scored > 70 were not dependent at discharge and had shorter than average length of stay. Patients who scored between 50 and 70 on the admission FIM had unpredictable outcomes. In terms of discharge destination, patients who were < 60 years old and had an admission FIM score > 70 were strongly associated with home discharge.

Stineman, Fiedler, Granger, and Maislin (1998) examined the records of 26,339 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. discharged from 252 inpatient rehabilitation facilities. They found that patients whose admission FIM scores were > 37 were able to eat, groom, dress their upper bodies and manage their bowels and bladder independently at discharge. Patients who scored > 55 were also able to bathe, dress their lower bodies and transfer onto a bed or chair and toilet. Additionally, most patients who had initial Motor-FIM scores > 62 and whose Cognitive-FIM scores were > 30 gained independence in most tasks, including transferring into the tub and climbing the stairs by the time of discharge. They also found that between 85% and 93% of 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. were discharged home.

Singh et al. (2000) administered the FIM to 81 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 1 month, 3 months, and 1 year post-stroke. Using stepwise linear regression, they found that lower total FIM scores at 1-month post-stroke were predictive of higher 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.
scores at 3 months post-stroke.

Cifu et al. (1997) compared 49 patients with traumatic brain injury who were employed at one-year follow-up with 83 patients who remained unemployed at one-year. They found that FIM scores at admission to rehabilitation were significantly associated with patients’ employment status one-year post head injury, such that patients who had returned to work one-year later had demonstrated significantly higher scores on the FIM at admission.

Tur, Gursel, Yavuzer, Kucukdeveci and Arasil (2003) 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 FIM in 102 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. admitted to rehabilitation units. The FIM was administered within 72 hours of admission and at discharge. Using a stepwise regression analysis, FIM scores at admission were found to be excellent predictors of FIM scores at discharge (0.90; p<0.001), indicating that the FIM can be used to predict functional recovery 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..

Whiting, Shen, Hung, Cordato & Chan (2010) examined predictors of 5-year survival in 166 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. (mean age 80 years), using the FIM. Using a logistic regression model, lower preadmission FIM scores were found to negatively predict 5-year survival of patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. (OR 1.04, 95%CI 1.1-2.0, P=0.01). In addition, total FIM scores were found to remain relatively stable from baseline to 5-year follow up in the 5-year survival group, however, FIM cognition scores were lower than baseline scores at the 5-year follow-up.

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 FIM 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) and neglect:
Granger, Hamilton, and Fielder (1992) found that at admission and discharge, functional scores for patients with right brain damage were slightly higher, but length of stay at the hospital and rate of community discharge were similar to that of patients who had left brain damage.

Alexander (1994) found that 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 had severe right brain damage had significantly less FIM change than patients with severe left brain damage.

Ring et al. (1997) found that patients with neglect or 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) had significantly higher FIM gains despite lower FIM admission scores. However, these patients also had a much longer length of stay at the hospital. It was also found that 96% of patients with right brain damage without neglect and 88% of patients with right brain damage and neglect were discharged home.

Oczkowski and Barreca (1993) found that patients with any degree of hemianopsiaBlindness in one half of the visual field of one or both eyes.
, parietal neglect, 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), or cognitive impairment had significantly lower FIM scores than those without these impairments, but unlike the results of Ring et al. (1997), hemianopsiaBlindness in one half of the visual field of one or both eyes.
, side of lesion, neglect 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) were not predictive of discharge destination.

Katz et al. (2000) examined correlations between the FIM (total, motor and cognitive scores) and the Lowenstein Occupational Therapy Cognitive Assessment (LOTCA – Orientation, Perception, Visuomotor Organisation and Thinking Operations subtest) in two subgroups of adults with right hemisphere 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=40 vs. patients without unilateral spatial neglect, n=21), 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.
analysis. Measures were taken on admission to and discharge from rehabilitation, and at 6-month follow-up. In the neglect group, adequate correlations were reported between FIM total and FIM motor, and LOTCA Visuomotor Organisation and Thinking Operations (range r=0.48 to -.51) at admission. Adequate to excellent correlations were reported between FIM total and FIM motor, and LOTCA Perception, Visuomotor Organisation and Thinking Operations (range r=0.48 to 0.75) at discharge. Excellent correlations were reported between FIM total and FIM motor and LOTCA Visuomotor Organisation and Thinking Operations tasks (range r=0.61 – 0.77) at follow-up. In the non-neglect group, poor to excellent correlations were reported between FIM cognitive and LOTCA scores (range r=0.05 to -.67) at admission. Moderate to excellent correlations were reported between FIM total and FIM motor, and LOTCA Visuomotor Organisation and Thinking Operations tasks at discharge and follow-up (range r=0.43 to 0.62).
Note: The FIM cognitive was not readministered at discharge or follow-up with this subgroup.

Construct:

Linacre et al. (1994) applied 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.
to the admission and discharge FIM scores of 14,799 patients. Two distinct aspects of disability were found within the FIM: Motor and Cognitive function.

Cavanagh, Hogan, Gordon, and Fairfax (2000) suggested that for post-stroke patients, a simple 2-factor model of the FIM may be insufficient to describe disability and may not measure within patient change adequately. The authors suggest that a three-dimensional FIM 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. be applied, which includes Self-care, Cognitive function, and Toileting as the major grouping of scales. They found that the 2-factor model only accounts for 66% of variance, whereas a 3-factor model accounted for more variance (74.2%).

Convergent/Discriminant:
Hobart et al. (2001) found that the total FIM and Motor-FIM scores correlated more strongly with the Office of Population Censuses and Surveys Disability Scales disability scores (r = 0.82 and 0.84, respectively), London Handicap Scale scores (r = 0.32 and 0.35, respectively), the SF-36 Physical component scores (r = 0.26 and 0.30, respectively) and the revised Wechsler Adult Intelligence Test-verbal IQ test (r = 0.35 and 0.27, respectively), than with measures of mental health status (SF-36 Mental component, r = 0.10 and 0.10, respectively) or psychological distress (General Health Questionnaire, r = 0.13 and r = 0.15, respectively). However, the Cognitive-FIM correlated most strongly with Office of Population Censuses and Surveys Disability scores (r = 0.43) and the revised Wechsler Adult Intelligence Test-verbal IQ scores (r = 0.51) and correlated poorly with the London Handicap Scale (r = 0.11), the SF-36 Physical and Mental components (r = 0.04 and r = 0.08, respectively), and the General Health Questionnaire (r = 0.01).

Giaquinto, Giachetti, Spiridigliozzi and Nolfe (2010) 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 FIM, Hospital Anxiety DepressionIllness involving the body, mood, and thoughts, that affects the way a person eats and sleeps, the way one feels about oneself, and the way one thinks about things. A depressive disorder is not the same as a passing blue mood or a sign of personal weakness or a condition that can be wished away. People with a depressive disease cannot merely “pull themselves together” and get better. Without treatment, symptoms can last for weeks, months, or years. Appropriate treatment, however, can help most people with depression.
Scale (HADS) and the World Health Organization Quality of Life scale (WHOQOL-100) in 107 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. (mean 5.6 months post-stroke). Assessments were performed at admission and discharge from a two-month rehabilitation program. As measured by Pearson’s correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficients, 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.
was found between FIM admission and FIM discharge scores (r=0.656, p<0.0001) and was not significantly influenced by gender. However, correlations between FIM discharge scores and HADS and WHOQOL-100 scores were influenced by gender. Among females 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.
was found between FIM discharge and HADS scores (r=-0.315, p<0.02) and FIM discharge and WHOQOL-100 scores (r=0.339, p<0.01), but the correlations among males’ scores were poor (r=0.139 and r=0.147 respectively).

Zwecker et al. (2002) reported an adequate correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the FIM cognitive subtest and the Lowenstein Occupational Therapy Cognitive Assessment (LOTCA) (r= 0.471, 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 the FIM cognitive subtest and the Mini Mental State Examination (MMSE) (r=0.666, p<0.001) in 66 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’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.
.

Known groups:
Dodds, Martin, Stolov and Deyo (1993) examined 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 FIM using data from 11,102 general rehabilitation inpatients (52% 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., 10% with orthopedic conditions, 10% with brain injury). FIM scores discriminated between groups based on spinal cord injury and strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. severity, and the presence of comorbid illness both at admission and discharge. The communication item of the FIM demonstrated most of the observed score difference.

Ring, Feder, Schwartz, and Samuels (1997) examined 151 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. admitted to a rehabilitation centre over a 2-year period. They found that the FIM was able to distinguish between patients with or without neglect and with or without 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) at both admission and discharge.

Ecological validity:

Cooke, McKenna, Fleming & Darnell (2006) examined the ecological validityRefers to the extent to which a measure captures behaviours that are reflective of those that would occur in a natural setting
of the Occupational Therapy Adult Perceptual ScreeningTesting for disease in people without symptoms.
Test (OT-APST) by comparing scores and completion time with the FIM motor and cognitive subtests in a sample of patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. (n=208). Significant but poor correlations were reported between FIM motor scores and 6 of the 7 OT-APST subscales (range r=0.26 to 0.41, p<0.01). Significant adequate correlations were reported between FIM cognitive scores and all 7 OT-APST subscales (range r=0.36 to 0.50, p<0.01). Significant poor to adequate negative correlations were also reported between the time taken to complete the FIM motor and cognitive subtests and the OT-APST (r=-0.27 and -0.33 respectively, p<0.01).

Responsiveness

The FIM is often compared to the Barthel Index, because the FIM was developed to be a more comprehensive and responsive measure of disability than the Barthel Index (van der Putten et al., 1999; Hobart & Thompson, 2001; Wallace, Duncan, & Lai, 2002; Hsueh et al., 2002).

Van der Putten et al. (1999) compared the Motor-FIM and total FIM to the Barthel Index in 201 patients with multiple sclerosis and 82 post-stroke patients undergoing inpatient neurorehabilitation. The Motor-FIM and total FIM demonstrated small effect sizes in the expected direction from admission to discharge in patients with multiple sclerosis (ES = 0.34 and ES = 0.30, respectively) and large effect sizes 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. (ES = 0.91 and ES = 0.82). The effect sizes for the Cognitive-FIM were not significant (ES = 0) in patients with multiple sclerosis and moderate 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. (ES = 0.61). Change scores for all scales in both disease groups were positive, indicating less disability on discharge than admission. Effect sizes on the Barthel Index were similar to those of the FIM in both patient groups, suggesting that the FIM might not have an advantage in terms of its responsivenessThe ability of an instrument to detect clinically important change over time.
to change.

Wallace et al. (2002) compared the responsivenessThe ability of an instrument to detect clinically important change over time.
of the Motor-FIM to the Barthel Index for strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. recovery between 1 and 3 months. The Barthel Index and Motor-FIM exhibited similar responsivenessThe ability of an instrument to detect clinically important change over time.
to change in this patient population (Motor-FIM, ES = 0.28; Standardized Response MeanThe standardized response mean (SRM) is calculated by dividing the mean change by the standard deviation of the change scores.
(SRM) = 0.62; AUC/ROC curve = 0.675).

Hsueh et al. (2002) compared the responsivenessThe ability of an instrument to detect clinically important change over time.
of the Motor-FIM, the original 10-item Barthel Index, and the 5-item short form Barthel Index in inpatients 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. receiving rehabilitation. The Barthel Index and Motor-FIM exhibited high responsivenessThe ability of an instrument to detect clinically important change over time.
(SRM = 1.2), indicating significant change.

Dromerick et al. (2003) assessed 95 consecutive admissions to 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 service for disability on admission and discharge. The Modified Rankin Scale and the International 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. Trial Measure were compared with the Barthel Index and the FIM. The number of patients for which each scale detected a clinically significant change in disability was determined. The SRM of the FIM was superior to that of the Barthel Index (2.18 versus 1.72) (change from admission to discharge from rehabilitation). The FIM was the most sensitive measure, detecting change in 91/95 subjects, including change in 18 patients in whom the Barthel Index detected no change.

Hobart and Thompson (2001) compared the responsivenessThe ability of an instrument to detect clinically important change over time.
of the modified Barthel Index, the FIM and the 30-item FIM plus Functional Assessment Measure (FIM + FAM) in 149 patients with various neurological disorders. The SRMs for the Barthel Index, the FIM, and the FIM + FAM scales measuring global, motor, and cognitive disability were found to be similar, suggesting that there is no advantage in responsivenessThe ability of an instrument to detect clinically important change over time.
of one measure over another (total FIM, SRM = 0.48; Motor-FIM, SRM = 0.54; Cognitive-FIM, SRM = 0.17).

Sharrack et al. (1999) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the FIM in 25 patients with multiple sclerosis. Patients were followed for 9 months, with assessments every 3 months. The total FIM demonstrated a poor 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 (ES = 0.46). A number of motor items (i.e. Eating, Grooming, Sphincter control, Bed/Chair/Wheelchair and Toilet Transfers, and Locomotion) had small to moderate responsivenessThe ability of an instrument to detect clinically important change over time.
(ES ranged from 0.25 for Toilet Transfer to 0.67 for Bed/Chair/Wheelchair Transfers). None of the cognitive items were responsive to change (ES ranged from 0.00 to 0.19).

Dodds, Martin, Stolov and Deyo (1993) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the FIM by analyzing the differences between admission and discharge FIM scores from 11,102 general rehabilitation inpatients (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. (52%), orthopedic conditions (10%), and brain injury (10%)). Significant functional gains were detected by the FIM (33% score improvement). The authors conclude that the FIM demonstrates some responsivenessThe ability of an instrument to detect clinically important change over time.
, but its ability to measure change over time needs further examination.

Hammond, Grattan, Sasser, Corrigan, Bushnik, and Zafonte (2001) examined FIM score changes over time in patients with traumatic brain injury. Significant differences in total FIM, Motor-FIM and Cognitive-FIM scores were reported between discharge from rehabilitation and follow-up at one year post-injury. Change between one and two years and one and five years was reported to be distributed across all items with most change observed in cognitive function.

Beninato, Gill-Body, Salles, Stark, Black-Schaffer and Stein (2006) defined the minimal clinically important difference (MCID) when using the FIM 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. population. The study included 113 patients from a rehabilitation unit at a long-term acute care hospital. The FIM was administered at admission and discharge; patient function was also assessed by attending physicians at the same time points using a 15-point integer scale where -7 indicated that a patient was “a very great deal worse”, 0 indicated “no change” and +7 indicated “a very great deal better”. Based on physicians’ ratings of clinical change made at discharge, change scores of 22, 17 and 3 for total FIM, motor FIM and cognitive FIM (respectively), were deemed to differentiate patients who demonstrated clinically important change from those who had not. Generalization of results is cautioned as the study only included patients receiving treatment at one centre and patient, caregiver or family assessments were not included in the ratings of important change.

References

• Alexander, M. P. (1994). Stroke rehabilitation outcomes: A potential use of predictive variables to establish levels of care. Stroke, 25(1), 128-134.
• Black, T. M., Soltis, T., Bartlett, C. (1999). Using the Functional Independence Measure instrument to predict stroke rehabilitation outcomes. Rehabilitation Nursing, 24(3), 109-114, 121.
• Beninato, M., Gill-Body, K.M., Salles, S., Stark, P.C., Black-Schaffer, R.M. & Stein, J. (2006). Determination of the Minimal Clinically Important Difference in the FIM instrument in patients with stroke. Archives of Physical Medicine and Rehabilitation, 87, 32-39.
• Brosseau, L., Wolfson, C. (1994). The inter-rater reliability and construct validity of the Functional Independence Measure for multiple sclerosis subjects. Clin Rehabi, 8, 107-115.
• Brock, K. A., Goldie, P. A., Greenwood, K. M. (2002). Evaluating the effectiveness of stroke rehabilitation: Choosing a discriminative measure. Arch Phys Med Rehabil, 83(1), 92-99.
• Cavanagh, S. J., Hogan, K., Gordon,V., Fairfax, J. (2000). Stroke-specific FIM models in an urban population. Journal of Neurological Nursing, 32, 17-21.
• Chau, N., Dalter, S., Andre, J. M., Patris, A. (1994). Inter-rater agreement of two functional independence scales: The Functional Independence Measure (FIM) and a subjective uniform continuous scale. Disabil Rehabil, 16(2), 63-71.
• Cifu, D., Keyser-Marcus, L., Lopez, E., Wehman, P., Kreutzer, J., Englander, J., High, W. (1997). Acute predictors of successful return to work 1 year after traumatic brain injury: A multicenter analysis. Archives of Physical Medicine and Rehabilitation, 78(2), 125-131.
• Cooke, D. M., McKenna, K., Fleming, J. & Darnell, R. (2006). Construct and ecological validity of the Occupational Therapy Adult Perceptual Screening Test (OT-APST). Scandinavian Journal of Occupational Therapy, 13, 49-61.
• Corrigan, J. D., Smith-Knapp, K., Granger, C. V. (1997). Validity of the functional independence measure for persons with traumatic brain injury. Arch Phys Med Rehabil, 78(8), 828-834.
• Daving, Y., Andren, E., Nordholm, L., Grimby, G. (2001). Reliability of an interview approach to the Functional Independence Measure. Clin Rehabil, 15(3), 301-310.
• Demers, L., Giroux, F. (1997). Validite de la Measure de l’independeance fonctionelle (MIF) pour les personnes agees suivies en readaptation. Canadian Journal on Aging/La revue canadienne du vieillissement, 16(4), 626-646.
• Dodds, T. A., Martin, D. P., Stolov, W. C., Deyo, R. A. (1993). A validation of the functional independence measurement and its performance among rehabilitation inpatients. Arch Phys Med Rehabil, 74(5), 531-536.
• Dromerick, A. W., Edwards, D. F., Diringer, M. N. (2003). Sensitivity to changes in disability after stroke: A comparison of four scales useful in clinical trials. Journal of Rehabilitation Research and Development, 40, 1-8.
• Fourn, L., Brosseau, L., Dassa, C., Dutil, E. (1994). Validation factorielle de la Mesure de l’independence functionelle (MIF) aupres de personnes atteintes de la sclerose en plaques. Journal de Readaptation Medicale, 14, 7-16.
• Gosman-Hedstrom, G., Blomstrand, C. (2004). Evaluation of a 5-level Functional Independence Measure in a longitudinal study of elderly stroke survivors. Disability & Rehabilitation, 26(7), 410-418.
• Granger, C. V., Deutsch, A., Linn, R. T. (1998). Rasch analysis of the Functional Independence Measure (FIM) Mastery Test. Arch Phys Med Rehabil, 79(1), 52-57.
• Granger, C. V., Hamilton, B. B., Keith, R. A., Zielezny, M., Sherwins, F. S. (1986). Advance in functional assessment for medical rehabilitation. Top Geriatr Rehabil, 1, 59-74.
• Granger, C. V., Cotter, A. C., Hamilton, B. B., Fiedler, R. C., Hens, M. M. (1990). Functional assessment scales: A study of persons with multiple sclerosis. Arch Phys Med Rehabil, 71, 870-875.
• Granger, C. V., Cotter, A. C., Hamilton, B. B., Fiedler, R. C. (1993). Functional assessment scales: A study of persons with stroke. Arch Phys Med Rehabil, 74(2), 133-138.
• Granger, C. V., Hamilton, B. B., Fiedler, R. C. (1992). Discharge outcomes after stroke rehabilitation. Stroke, 23(7), 978-982.
• Grey, N., Kennedy, P. (1993). The Functional Independence Measure: a comparative study of clinician and self rating. Paraplegia, 31, 457-461.
• Grimby, B., Gudjonsson, G., Rodhe, M., Sunnerhagen, K. S., Sundh, V., Ostensson, M. L. (1996). The Functional Independence Measure in Sweden: Experience for outcome measurement in rehabilitation medicine. Scandinavian Journal of Rehabilitation Medicine, 28, 51-62.
• Hall, K. M., Hamilton, B., Gordon, W. A., Zasler, N. D. (1993). Characteristics and comparisons of functional assessment indices: Disability Rating Scale, Functional Independence Measure and Functional Assessment Measure. J Head Trauma Rehabil, 8(2), 60-74.
• Hall, K. M., Mann, N., High, W., Wright, J., Kreutzer, J., Wood, D. (1996). Functional measures after traumatic brain injury: ceiling effects of FIM, FIM+FAM, DRS and CIQ. J Head Trauma Rehabil, 11(5), 27-39.
• Hammond, F. M., Grattan, K. D., Sasser, H., Corrigan, J. D., Bushnik, T., Zafonte, R. D. (2001). Long-term recovery course after traumatic brain injury: A comparison of the Functional Independence Measure and Disability Rating Scale. Journal of Head Trauma, 16(4), 318-329.
• Hamilton, B. B., Laughlin, J. A., Fiedler, R. C., Granger, C. V. (1995). Interrater reliability of the 7-level functional independence measurement (FIM). Scand J Rehabil Med, 27, 253-256.
• Hamilton, B. B., Laughlin, J. A., Fiedler, R. C., Granger, C. V. (1994). Interrater reliability of the 7-level functional independence measure (FIM). Scand J Rehabil, 26, 115-119.
• Heinemann, A. W., Linacre, J. M., Wright, B. D., Hamilton, B. B., Granger, C. (1994). Prediction of rehabilitation outcomes with disability measures. Arch Phys Med Rehabil, 75(2), 133-143.
• Hobart, J. C., Lamping, D. L., Freeman, J. A., Langdon, D. W., McLellan, D. L., Greenwood, R. J., Thompson, A. J. (2001).Which disability scale for neurologic rehabilitation? Neurology, 57, 639-644.
• Hobart, J. C., Thompson, A. J. (2001). The five item Barthel index. J Neurol Neurosurg Psychiatry, 71, 225-230.
• Hsueh, I-P., Lin, J-H., Jeng, J-S., Hsieh, C-L. (2002). Comparison of the psychometric characteristics of the functional independence measure, 5 item Barthel index, and 10 item Barthel index in patients with stroke. Journal of Neurology Neurosurgery and Psychiatry, 73, 188-190.
• Inouye, M., Kishi, K., Ikeda, Y., Takada, M., Katoh, J., Iwahasi, M., Hayakawa, M., Ishihara, K., Sawamura, S., Kazumi, T. (2000). Prediction of functional outcome after stroke rehabilitation. American Journal of Physical Medicine and Rehabilitation, 79(6), 513-518.
• Jaworski, D. M., Kult, T., Boynton, P. R. (1994). The Functional Independence Measure: A pilot study comparison of observed and reported ratings. Rehabil Nur Res, 3, 141-147.
• Katz, N., Hartman-Meier, A., Ring, H. & Soroker, N. (2000). Relationships of cognitive performance and daily function of clients following right hemisphere stroke: Predictive and ecological validity of the LOTCA battery. Occupational Therapy Journal of Research, 20, 3-17.
• Keith, R. A., Granger, C. V., Hamilton, B. B., Sherwin, F. S. (1987). The functional independence measure: A new tool for rehabilitation. Adv Clin Rehabil, 1, 6-18.
• Kidd, D., Stewart, G., Baldry, J., Johnson, J., Rossiter, D., Petruckevitch, A., Thompson, A. J. (1995). The Functional Independence Measure: A comparative validity and reliability study. Disabil Rehabil, 17(1), 10-14.
• Küçükdeveci, A. A., Yavuzer, G., Elhan, A. H., Sonel, B. (2001). Adaptation of the Functional Independence Measure for use in Turkey. Clinical Rehabilitation, 15(3), 311-319.
• Kwon, S., Hartzema, A. G., Duncan, P. W., Min-Lai, S. (2004). Relationship among the Barthel Index, the Functional Independence Measure, and the Modified Rankin Scale. Stroke, 35, 918-923.
• Linacre, J. M., Heinemann, A. W., Wright, B. D., Granger, C. V., Hamilton, B. B. (1994). The structure and stability of the Functional Independence Measure. Arch Phys Med Rehabil, 75(2), 127-132.
• McDowell, I., Newell, C. (1996). Measuring health: a guide to rating scales and questionnaires (pp. 63-67). (2nd Ed.), New York: Oxford University Press.
• Mokler, P. J., Sandstrom, R., Griffin, M., Farris, L., Jones, C. (2000). Predicting discharge destination for patients with severe motor stroke: Important Functional Tasks. Neurorehabilitation and Neural Repair, 14(3), 181-185.
• Msall, M. E., DiGaudio, K., Rogers, B. T., LaForest, S., Catanzaro, N. L., Campbell, J., Wilczenski, F., Duffy, L. C. (1994). The Functional Independence Measure for Children (WeeFIM). Conceptual basis and pilot use in children with developmental disabilities. Clin Pediatr (Phila), 33(7), 421-430.
• Naghdi S, Ansari NN, Raji P, Shamili A, Amini M, Hasson S. Cross-cultural validation of the Persian version of the Functional Independence Measure for patients with stroke. Disabil Rehabil. 2016;38(3):289-98. doi: 10.3109/09638288.2015.1036173. https://www.ncbi.nlm.nih.gov/pubmed/25885666
• Oczkowski, W. J., Barreca, S. (1993). The functional independence measure: Its use to identify rehabilitation needs in stroke survivors. Arch Phys Med Rehabil, 74(12), 1291-1294.
• Ottenbacher, K. J., Hsu, Y., Granger, C. V., Fiedler, R. C. (1996). The reliability of the functional independence measure: a quantitative review. Arch Phys Med Rehabil, 77(12), 1226-1232.
• Ottenbacher, K. J., Mann, W. C., Granger, C. V., Tomita, M., Hurren, D., Charvat, B. (1994). Inter-rater agreement and stability of functional assessment in the community-based elderly. Arch Phys Med Rehabil, 75(12), 1297-1301.
• Pollak, N., Rheault, W., Stoecker, J. L. (1996). Reliability and validity of the FIM for persons aged 80 years and above from a multilevel continuing care retirement community. Arch Phys Med Rehabil, 77(10), 1056-1061.
• Ring, H., Feder, M., Schwartz, J., Samuels, G. (1997). Functional measures of first-stroke rehabilitation inpatients: Usefulness of the Functional Independence Measure total score with a clinical rationale. Arch Phys Med Rehabil, 78(6), 630-635.
• Segal, M. E., Schall, R. R. (1994). Determining functional/health status and its relation to disability in stroke survivors. Stroke, 25, 2391-2397.
• Segal, M. E., Ditunno, J. F., Staas, W. E. (1993). Interinstitutional agreement of individual functional independence measure (FIM) items measured at two sites on one sample of SCI patients. Paraplegia, 31(10), 622-631.
• Segal, M. E., Gillard, M., Schall R. (1996). Telephone and in-person proxy agreement between stroke patients and caregivers for the functional independence measures. Am J Phys Med Rehabil, 75(3), 208-212.
• Sharrack, B., Hughes, R. A., Soudain, S., Dunn, G. (1999). The psychometric properties of clinical rating scales used in multiple sclerosis. Brain, 122(1), 141-159.
• Singh, A., Black, S. E., Herrmann, N., Leibovitch, F. S., Ebert, P. L., Lawrence, J., Szalai, J. P. (2000). Functional and neuranatomic correlations in poststroke depression. Stroke, 31, 637-644.
• Stineman, M. G., Fiedler, R. C., Granger, C. V., Maislin, G. (1998). Functional task benchmarks for stroke rehabilitation. Archives of Physical Medicine and Rehabilitation, 79, 497-504.
• Teasell, R., Foley, N. C., & Salter K. (2011). EBRSR: Evidence-Based Review of Stroke Rehabilitation. 13th ed. London (ON): EBRSR.
• Timbeck, R. J., Spaulding, S. J. (2003). Ability of the Functional Independence Measure to predict rehabilitation outcomes after stroke: A review of the literature. Physical & Occupational Therapy in Geriatrics, 22(1), 63-76.
• Tur, B.S., Gursel, Y.K., Yavuzer, G., Kucukdeveci, A. & Arasil, T. (2003). Rehabilitation outcome of Turkish stroke patients: In a team approach setting. International Journal of Rehabilitation Research, 26, 271-277.
• van der Putten, J. J., Hobart, J. C., Freeman, J. A., Thompson, A. J. (1999). Measuring change in disability after inpatient rehabilitation: Comparison of the responsiveness of the Barthel Index and the Functional Independence Measure. Neurol Neurosurg Psychiatry, 66, 480-484.
• Wallace, D., Duncan, P. W., Lai, S. M. (2002). Comparison of the responsiveness of the Barthel Index and the motor component of the Functional Independence Measure in stroke: the impact of using different methods for measuring responsiveness. J Clin Epidemiol, 55, 922-928.
• Ween, J. E., Mernoff, S. T., Alexander, M. P. (2000). Recovery rates after stroke and their impact on outcome prediction. Neurorehabilitation and Neural Repair, 14(3), 229-235.
• Whiting, R., Shen, Q., Hung, W.T., Cordato, D. & Chan, D.K.Y (2010). Predictors for 5-year survival in a prospective cohort of elderly stroke patients. Acta Neurologica Scandinavica, DOI: 10.1111/j.1600-0404.2010.01476.
• Zwecker, M., Levenkrohn, S., Fleisig, Y., Zeilig, G., Ohry, A., & Adunsky, A. (2002). Mini-Mental State Examination, cognitive FIM instrument, and the Loewenstein Occupational Therapy Cognitive Assessment: relation to functional outcome of stroke patients. Archives of Physical Medicine and Rehabilitation, 83, 342-345.

See the measure

Click here to find a copy of the FIM (the original comes from the following website: http://www.va.gov/vdl/documents/Clinical/Func_Indep_Meas/fim_user_manual.pdf)

http://www.udsmr.org