Assessment of Motor and Process Skills

Last Updated

April 26, 2019

Purpose

The Assessment of Motor and Process Skills (AMPS) is an observational assessment that measures the performance quality of tasks related to activities of daily living (ADL) in a natural environment. The AMPS is designed to examine interplay between the person, the ADL task and the environment.

Link to Instrument

Instrument Details

Acronym AMPS

Area of Assessment

Activities of Daily Living
Attention & Working Memory
Executive Functioning
Insight
Processing Speed
Reasoning/Problem Solving
Balance – Vestibular
Coordination
Functional Mobility
Gait
Occupational Performance

Assessment Type

Performance Measure

Administration Mode

Paper & Pencil

Cost

Not Free

Actual Cost

$795.00

Cost Description

Fee for certification through online course. Cost ranges from $795-$995

Stroke

Pediatric Disorders

Older Adults and Geriatric Care

Alzheimer's Disease and Progressive Dementia

Mixed Populations

Mental Health

The AMPS assesses the quality of the person’s ADL performance by rating the effort, efficiency, safety, and independence of 16 ADL motor and 20 ADL process skill items. The skills are consistent with the goal-directed actions defined under the Activities and Participation domains of the International Classification of Functioning, Disability and Health.
The smallest observable action of an occupation performed is called performance skills. ADL motor skills are observed when an object is moved or when one moves oneself. ADL process skills rate the competency when one selects and interacts with tools and materials and changes performance when problems are encountered.
The 16 ADL motor skill items are divided into 4 domains (Body Position, Obtaining and Holding Objects, Moving Self and Objects, Sustaining Performance). The 20 ADL process skill items are divided into 5 domains (Sustaining Performance, Applying Knowledge, Temporal Organization, Organizing Space and Objects, Adapting Performance)
Item-level scores range from 1 = No Problem to 6 = Inordinate; cannot test
The AMPS is administered in four phases. Phase I = Administration Preparation; Phase II = Occupational therapy interview; Phase III = Observe and implement a performance analysis; Phase IV = Score the AMPS observation
After AMPS administration, the clinician interprets AMPS reports to define and interpret reasons for the person's ineffective ADL performance. The team uses this information to plan and implement occupation-based interventions, then reevaluate progress for enhanced ADL task performance
The AMPS manual provides further information regarding detailed steps for AMPS administration, cultural activity considerations, situational circumstances that may impact administration, and additional information needed to properly administer the assessment.

Number of Items

36 items (16 ADL motor skill items, 20 ADL process skill items)

AMPS Manual, Volumes 1 and 2 (included in the course cost)
AMPS Score Forms (free to download)
Pen or pencil
Highlighter
Sticky notes or page markers to denote specific sections of manual
Blank paper for notes

30-40 minutes

AMPS can be administered in any task-relevant setting

Required Training

Training Course

Preschool Children

2 - 5

years

Child

6 - 12

years

Adolescent

13 - 17

years

Adult

18 - 64

years

Elderly Adult

65 +

years

Instrument Reviewers

Jenine Ampudia, OTS, University of Illinois at Chicago

Courtney Heidle, OTS, University of Illinois at Chicago

Johnny Sok, OTS, University of Illinois at Chicago

Jennifer Yi, OTS, University of Illinois at Chicago

ICF Domain

Activity

Measurement Domain

Activities of Daily Living
Cognition
Motor

Considerations

AMPS items and raw scores are never valid, must be computer generated

Client must be marginally motivated or willing to perform this simple ADL task

Client must be familiar with the selected ADL task

When using AMPS with pediatric populations, the typical and age-appropriate occupational performance must be considered

Clients with severe cognitive or language impairments are allowed to practice the ADL task to assure understanding. If practices, score must be cautiously interpreted

If client has never learned how to perform ADL task, there is a chance to learn and practice the ADL task before AMPS is completed

AMPS score forms are available in English, German, Spanish, French, Dutch, and Slovenian

Test/Retest Reliability

Schizophrenia: (Haslam et al., 2010; n = 20; Mean Age = 44.3 (8.49) years)

Acceptable test-retest reliability (ICC = .60-.80)

Psychiatric Disorders: (Pan and Fisher, 1994; n = 60; Mean Age = 37.9 (14.9); Sample included diagnosis of affective disorders, delusional disorders, schizophrenia, or alcohol hallucinosis)

Excellent test-retest reliability (ICC = .95)

Internal Consistency

Schizophrenia: (Haslam et al., 2010)

Adequate internal consistency (Cronbach's alpha = .79)

Criterion Validity (Predictive/Concurrent)

Predictive validity

Schizophrenia (Haslam et al., 2010)

Significant ability of AMPS Global Process Skills to predict employment levels for people living with schizophrenia (p = .03)

Significant ability of AMPS Sustaining Performance Process Skill to predict employment levels for people living with schizophrenia (p = .05)

Psychiatric Disorders: (Merritt, 2011; n = 8556; Mean Age = 55.1(17.9) years; Subset of data from AMPS Project International database)

Poor ability of AMPS Motor score to predict ADL motor performance (AUC = .68)

Adequate ability of AMPS Process score to predict ADL process performance (AUC = .77)

Psychiatric Conditions associated with cognitive impairments: (McNulty & Fisher, 2001; n = 20; Mean Age = 58 (16.05) years)

Excellent ability to predict motor and ADL process ability measures to participants’ safety at home (r = .75)

Construct Validity

Discriminant Validity

Psychiatric Disorders: (Pan & Fisher, 1994; n = 60; Sample includes diagnosis of affective disorders, delusional disorders, schizophrenia, or alcohol hallucinosis)

Significant ability to differentiate between persons with psychiatric disorders and persons without (p ≤ 0.001)

Cut-Off Scores

Stroke: (Bernspang & Fisher, 1995; n =230; Individuals with history of RCVA (n = 71), history of LCVA (n = 76), and nondisabled (n = 83))

Process scores below the 1.0 log-odd probability units (logit) scale indicate poorer process functioning

Motor scores below the 2.0 log-odd probability units (logit) scale indicate poorer motor functioning

Test/Retest Reliability

Stroke: (Fisher & Bray Jones, 2010 as cited in Poulin et al., 2013; n = 8801; subset of AMPS Project International database; adults with hemispheric stroke)

Excellent test-retest reliability: (Motor: r = .88 - .91; Process: r = .86- .90)

Internal Consistency

Stroke: (Fisher & Bray Jones, 2010 as cited in Poulin et al., 2013)

Excellent: Cronbach's alpha for motor score = 0.92
Excellent: Cronbach's alpha for process score = 0.91
*Scores higher than .9 may indicate redundancy in the scale questions.

Criterion Validity (Predictive/Concurrent)

Concurrent validity

Stroke (Marom, Jarus & Josman, 2006; n= 30; Individuals in their first week home during stroke recovery)

Moderate associations with the Large Allen Cognitive Levels (r = 0.57 for motor; r = .66 for process)

Predictive validity:

Hemispheric Stroke: (Merritt, 2011; n = 17568; Mean Age = 61.7 (20.6); Subset of AMPS Project International database: Individuals with hemispheric stroke ( n = 8801) and individuals with other neurological conditions ( n = 8767)

Adequate ability of AMPS Motor score to predict ADL motor performance (AUC = .82)
Adequate ability of AMPS Process score to predict ADL process performance (AUC= .82)

Stroke: (Dickerson, Reistetter & Trujullo, 2010; n = 46; Mean Age = 71.67 (10.76); Community sample referred for driving assessment)

Excellent: Scores on AMPS correctly predict those who fail on-road evaluation or needed additional evaluation 87% of the time (p < 0.001)

Construct Validity

Convergent Validity

Stroke (Kizony & Katz, 2002; n = 30; Mean Age = 71.3 years; Inpatient acute care, 4-5 weeks Post-Stroke)

Moderate relationship between various cognitive assessments and AMPS process scores

Responsiveness

Stroke: (Bjorkdahl et al., 2006; n = 58; Assessed at discharge, three weeks, three months, and one year after discharge; Swedish sample)

Adequate, positive changes were found between discharge and one year after discharge for both motor scores (x̅ = 1.45, 2.18) and process scores (x̅ = 1.00, 1.55)

Stroke: (Bernspang & Fisher, 1995)

Significant differences between individuals who had a previous stroke (RCVA and LCVA) when compared to non-disabled individuals for IADL performance (p ≲ .05)

Standard Error of Measurement (SEM)

Geriatric: (Doble, Fisk, Lewis & Rockwood, 1999; n = 55; Mean Age = 77.9 (7.0) years; Community-dwelling elderly adults)

Measurement error accounted for 22% of the differences in subjects’ ADL ability measures

Normative Data

Geriatric: (Fioravanti et al., 2012; n = 54; Mean Age = 80 (8.6) years; Mean Length of Stay = 24 (12) days; Canadian sample in a geriatric and neuro-oncology inpatient rehabilitation unit

Admission

M(SD)

Discharge

M(SD)

AMPS motor

0.14 (0.42)

0.84 (0.51)

AMPS process

0.40 (0.47)

0.91 (0.54)

Geriatric: (Doble, Fisk, Lewis & Rockwood, 1999)

	Time 1			Time 2
	Mean	SD	Range	Mean	SD	Range
AMPS motor	1.7	0.9	-0.1 to 4.0	1.7	0.9	-0.2 to 3.7
AMPS process	1.0	0.7	-1.3 to 2.4	1.1	0.8	-0.5 to 2.7
POMS	2.0	2.3	0 to 12	1.9	2.2	0 to 8

Test/Retest Reliability

Geriatric with cognitive impairments: (Doble, Fisk, Lewis & Rockwood, 1999; Rockwood, Doble, Fisk, MacPherson, & Lewis as cited in Fisher, 2003)

Excellent test-retest reliability: (Motor Scale r = 0.88 - 0.9; Process Scale r = 0.86 - 0.87)

Geriatric: (Doble, Fisk, Lewis & Rockwood, 1999)

Excellent test-retest reliability: (Motor: r = 0.88; Process: r = 0.86)

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Older adults: (Wales, Clemson, Lannin & Cameron, 2016; Mean Age > 70 years; Analysis of 56 papers with RCT design detailing functional assessments for older adults)

Moderate concurrent validity with AMPS motor and FIM motor scores (r = 0.54, r = 0.62 p <.001).

Moderate concurrent validity with AMPS process and FIM cognitive ratings (r = 0.56, r = 0.62, p<0.001).

Geriatrics: (Fioravanti et al., 2012)

Moderate correlation between the FIM motor scores and AMPS motor measures (r = 0.54, p<0.001) and between the FIM cognitive scores and the AMPS process measures (r = 0.56, p<0.001).

Weak correlation between the FIM motor and AMPS motor measures at time of discharge (r = 0.29, p = 0.035).

Moderate correlation between FIM cognitive scores and the AMPS process measures (r = 0.48, p < 0.001).

No significant correlation in comparison of the amount of change detected by each instrument.

No significant correlation for changes in FIM motor scores changes detected using the AMPS motor scale (r = 0.01, p = 0.951).

No significant correlation for changes detected by the FIM cognitive scale and those detected by the AMPS process scale (r = 0.19, p = 0.180).

Geriatric with Memory Impairments: (Robinson & Fisher, 1996)

Low significant correlation between CAMCOG and AMPS motor ability (r = -0.04, p = .38)

Low significant correlation between MMSE and AMPS motor ability (r = -0/01, p = 0.47)

Moderate correlation between FIM Motor and AMPS motor ability (r = 0.62, p<0.001)

Low significant correlation between FIM Cognition and AMPS motor ability (r = -0.07, p=0.32)

Moderate correlation between CAMCOG and AMPS process ability (r = 0.65, p<0.001)

Moderate correlation between MMSE and AMPS process ability (r = 0.67, p<0.001)

Low significant correlation between FIM Motor and AMPS process ability (r = 0.13, p=0.19)

Moderate correlation between FIM Cognition and AMPS process ability (r = 0.62, p<0.001)

Construct Validity

Older Adults: (Wales, Clemson, Lannin & Cameron, 2016)

Moderate support for construct validity in older adult populations

Floor/Ceiling Effects

Geriatric with Memory Impairments: (Robinson & Fisher, 1996; n = 51; Mean Age = 75.4 (9.56) years)

No ceiling effects found for the AMPS motor and process scales

Responsiveness

Geriatric: (Fioravanti et al., 2012)

Comparison of sensitivity to change from admission to discharge at inpatient rehabilitation:
- AMPS motor: Effect size (d = 2.14), Large positive effect
- AMPS process: Effect size (d = 1.59), Large positive effect

Cut-Off Scores

Older Adults with Dementia of the Alzheimer’s Type (DAT) (Hartman, Fisher & Duran, 1999; n = 788; Independent Older Adults ( n = 329, Mean Age = 70.5 (5.9)), Older Adults with minimal DAT ( n = 167, Mean Age = 71.2 (9.7)), Older Adults with moderate DAT ( n = 292, Mean Age = 74.5 (8.4)); Sample selected from AMPS database)

Scores below 2.0 logit for motor scale indicate increased need for assistance to live in the community (correct classification rate = 64%; n= 788)
Scores below 1.0 logit for motor scale indicate increased need for assistance to live in the community (correct classification rate = 94%; n= 789)

Normative Data

Older Adults with Dementia of the Alzheimer’s Type (DAT) (Hartman, Fisher & Duran, 1999)

	Non-disabled older adults	Minimal DAT	Mod-Max DAT
AMPS Motor
Mean	2.8	2.4	1.9
SD	0.5	0.8	0.8
Range	1.4-4.0	0.3-4.0	0.1-3.8
AMPS Process
Mean	1.7	0.6	-0.2
SD	0.4	0.4	0.8
Range	0.7-2.9	-0.5 - 1.6	-3.0 - 1.4

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Geriatric with Alzheimer’s disease: (Doble, Fisk & Rockwood, 1999; n = 26; Mean Age = 76.8 (6.6) years; Canadian sample)

Moderate agreement between AMPS ADL process scale and Older Americans Resources and Services (OARS) (k = 0.36).

Older Adults with Dementia (Fisher & Jones, 2012; n = 5417)

Moderate correlation between AMPS and FIM (r = -0.62)

Predictive

Dementia (Merritt, 2011; n = 2488; subset of AMPS Project International database)

Adequate ability of AMPS Motor score to predict ADL motor performance (AUC = .78)
Excellent ability of AMPS Process score to predict ADL process performance (AUC = .92)

Construct Validity

Older Adults with Dementia of the Alzheimer’s Type (DAT) (Hartman, Fisher & Duran, 1999)

Significant main effect between AMPS motor score and functional levels of individuals (p < 0.0001)

Significant main effect between AMPS process score and functional levels of individual (p < 0.0001)

Cut-Off Scores

School-Aged Children with Identified Disability: (Atchinson, Fisher & Bryze, 1998; n = 54; Mean Age = 4.0 (0.7) years; Students receiving occupational therapy for an identified disability (n = 32) and typically developing students as comparison group (n = 22))

Although ideal values are MnSq = 1.0 and z = 0, MnsQ < 1.4 and z < 2 are used because the values are based on criteria to develop the AMPS

Test/Retest Reliability

School-Aged Children with Identified Disability or At-Risk: (Munkholm, Berg, Lofgren & Fisher, 2010; n = 984; Age Range 3-13; Students from North America, Australia, New Zealand, United Kingdom and Nordic countries)

DIF (Differential Item Functionality) has no difference between regions if (-0.55) < logit < (0.55)

Interrater/Intrarater Reliability

School-Aged Children with Identified Disability: (Atchinson, Fisher & Bryze, 1998)

Strong intrarater reliability. (MnSq = 1.0, z = 0)

Criterion Validity (Predictive/Concurrent)

School-Aged Children: (Fingerhut et. al, 2002; n = 42; Age Range 5 – 7; Kindergarten students from five public schools)

Adequate predictive ability of Peabody Developmental Motor Scale -- Fine Motor (PDMS-FM) when using school AMPS motor and process scale (r = .45, r = .35)

Construct Validity

Children with No Known Disabilities: (Peny-Dahlstrand, Gosman-Hedstrom & Krumlinde-Sundholm, 2010)

Low significant age by region interaction effect; F = 1.455 (df 12), p = 0.133 but there was a significant difference between the regions F = 30.80 (df 1), p = <0.001 with Nordic children having the higher measures.

Low significance age by region interaction effect, ANOVA comparison of variance for ADL process ability F = 1.086 (df 12) p = 0.367 and

Low significant differences between the regions, F = 1.88 (df 1), p = 0.170.

Developmental Delays (Kang et al., 2008; n = 33; Mean Age = 6.1 (1.9) years; Korean sample)

Moderate correlations between AMPS-M and COPM-P (r = 0.67)

Moderate correlations between AMPS-P and COPM-S (r = 0.64)

Children With or Without Mild Disabilities: (Gantschnig, Page, Nilsson & Fisher, 2013; n = 10,998; Mean Age = 8.7 (3.2) years; Sample selected from the international AMPS database)

Poor significance between groups in mean ADL motor ability (p = .308, t = 0.503)

Excellent significance main effect for age (p < .001, t = 26.187)

Excellent significance for Age x Group interaction effect (p <.001, t = -6.612)
Excellent significance between two groups in mean ADL process ability measures (p < .001, t = -4.296)

Content Validity

Children with No Known Disabilities (Poulson, 1996; n = 162)

Goodness of fit; 90% to AMPS-M, 95% to AMPS-P

Responsiveness

Children With or Without Mild Disabilities: (Gantschnig, Page, Nilsson & Fisher, 2013)

Small Change (Cohen’s d = 0.17) for 4 year olds in ADL motor ability

Moderate Change (Cohen’s d = 0.32 to 0.50) for 5-8 year olds in ADL motor ability

Big Change (Cohen’s d = 0.81 to 0.98) for 12-15 year olds in ADL motor ability
Big Change (Cohen’s d = 0.83 to 1.26) for 6-15 year olds in ADL process ability

Standard Error of Measurement (SEM)

Children with No Known Disabilities: (Peny-Dahlstrand, Gosman-Hedstrom & Krumlinde-Sundholm, 2012; n = 4613; Age Range 3-15 years; Subset of the AMPS Project International Database, North American (n = 2239) and Nordic (n = 2374) children )

Confidence interval of 95% = (+ 0.49) and (+ 0.39) logits respectively. To be considered relevant, difference should exceed + 1.96 SEM.

No age group had differences in logits for ADL motor ability larger than 1.96 SEM (+ 0.49)
No significant difference between regions

Cut-Off Scores

Community Dwelling Adults (Merritt, 2011; n = 38,540, Randomly-selected subset of AMPS Project International database)

Process scores below the 1.0 logit scale indicate higher need for assistance (sensitivity = .81, specificity = .7)
Motor scores below the 1.5 logit scale indicate higher need for assistance (sensitivity = - .67, specificity = .72)

Normative Data

Community Dwelling Adults (Merrit, 2011)

	Independent Adults (n = 10,458)	Adults needing Min Assist (n = 23,679)	Adults needing max assist (n = 30,329)
AMPS Motor
Mean	1.83	1.30	0.64
SD	0.69	0.76	0.98
Range	-.03- 3.91	-0.76	-3.05- 3.46
AMPS Process
Mean	1.45	0.99	0.35
SD	0.51	0.48	0.96
Range	0.07-2.91	-0.36-2.35	-2.75-2.05

Mixed Population: (Gantschnig, Page & Fisher, 2012; n = 145489; Mean Age = 54.06 (24.43) years; Sample from the international AMPS database)

	n	Age, years (SD)	ADL Motor Ability	ADL Process Ability
North America	23441	53.28 (25.82)	1.21 (0.96)	0.78 (0.72)
UK/Ireland	29670	53.66 (24.01)	1.21 (0.96)	0.69 (0.70)
Nordic	47445	55.02 (23.72)	1.14 (0.93)	0.84 (0.69)
Other Europe	15057	57.80 (22.93)	0.97 (0.91)	0.69 (0.68)
Australia/New Zealand	13329	50.15 (24.48)	1.22 (0.96)	0.75 (0.68)
Asia	15210	53.12 (25.86)	0.90 (0.95)	0.70 (0.66)
Middle Europe	1346	50.27 (24.66)	0.84 (0.89)	0.59 (0.64)
Total	145489	54.06 (24.43)	1.13 (0.95)	0.76 (0.69)

Test/Retest Reliability

Mixed Population: (Fisher & Jones, 2012; n = 148158; Age Range = 3 - 103; Sample from international AMPS database)

Excellent test-retest reliability of the AMPS at predicting AMPS-motor (r = 0.9-0.91)
Excellent test-retest reliability of the AMPS-process scores (r = 0.87-0.90)

Interrater/Intrarater Reliability

Community-Dwelling: (Goto, Fisher & Mayberry, 1996; n = 10; Mean Age = 28.9 (3.98) years; Mean time living in United States = 12.4 (8.8) months; Japanese sample living in the United States for less than 3 years)

Excellent interrater reliability (proportion of individual misfitting ratings was less than 2.5% (t = 3) )

Community-Dwelling: (Fisher, Liu, Velozo & Pan, 1992; n = 20; Mean Age = 28.5 (3.32) years; Non-disabled Taiwanese sample living in United States for less than 3 years)

Excellent intrarater reliability (r = 0.93)

Internal Consistency

Mixed Population: (Fisher & Jones, 2012)

Excellent internal consistency. ADL motor (r = 0.92)
Excellent internal consistency. ADL process (r = 0.91)

Criterion Validity (Predictive/Concurrent)

Mixed Population: (Fisher & Jones, 2012)

Moderate-Excellent correlations between AMPS and SIB (r = 0.62 - 0.85)

Construct Validity

Community Dwelling Adults (Merritt, 2011)

Fair discriminating value for determining community independence for AMPS motor (AUC = .78)
Good discriminating value for determining community independence for AMPS process (AUC = .84)

Content Validity

Mixed Population: (Fisher & Jones, 2012)

Extensive literature review; filming and observation of wide range of ADL tasks; Rasch model
Acceptable goodness-of-fit of tasks, skill items and participants

Face Validity

Mixed Population: (Gantschnig, Page & Fisher, 2012)

Only one ADL item, Aligns, demonstrated differential item functioning (DIF), but did not result in differential test functioning (DTF)
AMPS is free of cross-regional bias when used in middle Europe

Responsiveness

Community Dwelling Adults (Merritt, 2011)

Clinically significant associations, large effect size with AMPS motor scores and global functional level (p < 0.01; Cohen’s d= .213)

Clinically significant associations, large effect size with AMPS process scores and global functional level (p< 0.01; Cohen’s d= .331)

Normative Data

Multiple Sclerosis: (Doble et al., 1994; n = 44Mean Age = 44.5 (12.3) years, Mean Duration of Self-Reported MS = 19.9 (12.4) years)

	MS Group			Non-disabled Control
	M	SD	Range	M	SD	Range
Motor	2.20	1.32	-0.28 to 4.67	4.05	.87	2.26 to 5.61
Process	1.37	.53	0.51 to 2.22	2.08	.46	1.70 to 2.08

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Purpose

Link to Instrument

Area of Assessment

Assessment Type

Administration Mode

Cost

Actual Cost

Cost Description

Number of Items

Required Training

Instrument Reviewers

ICF Domain

Measurement Domain

Considerations

Test/Retest Reliability

Internal Consistency

Criterion Validity (Predictive/Concurrent)

Construct Validity

Cut-Off Scores

Test/Retest Reliability

Internal Consistency

Criterion Validity (Predictive/Concurrent)

Construct Validity

Responsiveness

Standard Error of Measurement (SEM)

Normative Data

Test/Retest Reliability

Criterion Validity (Predictive/Concurrent)

Construct Validity

Floor/Ceiling Effects

Responsiveness

Cut-Off Scores

Normative Data

Criterion Validity (Predictive/Concurrent)

Construct Validity

Cut-Off Scores

Test/Retest Reliability

Interrater/Intrarater Reliability

Criterion Validity (Predictive/Concurrent)

Construct Validity

Content Validity

Responsiveness

Standard Error of Measurement (SEM)

Cut-Off Scores

Normative Data

Test/Retest Reliability

Interrater/Intrarater Reliability

Internal Consistency

Criterion Validity (Predictive/Concurrent)

Construct Validity

Content Validity

Face Validity

Responsiveness

Normative Data

Bibliography

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