Mobility, Work and Assistive Technology
Text-only Version
Mobility, Work and Assistive Technology
Prepared by:
Gerry E. Hendershot
Lita H. Jans
Diane S. Shinberg
For:
129th Annual APHA Meeting
Atlanta, GA, October 23, 2001
InfoUse
AT Data Collection, #H224B990011
National Institute on Disability and Rehabilitation Research
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Slide 2
Purposes of study -1
- Explore relationship between assistive technology (AT) use & labor force participation (LFP) among people with mobility limitations.
- Aggregate 3 years of National Health Interview Survey (NHIS) data
- Interpret findings using International Classification of Functioning Disability & Health (ICF)
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Slide 3
Purposes of study -2
- Understand some characteristics and "behavior" of NHIS AT variable.
- Same AT question asked in all states on the Behavioral Risk Factor Surveillance Survey (BRFSS) core questionnaire 2001, and used as objective in Healthy People 2010.
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Slide 4
Schematic representation of ICF
- Level I: Health Factors
- Level II:
- Body Structure & Function
- Activity
- Participation
- Level III:
- Environmental Factors
- Personal Factors
Image: Flow chart
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Slide 5
Schematic representation of study variables
- Level I: Health Factors
- Level II:
- Body Structure & Function
- Activity: Mobility
- Participation: Labor Force
- Level III:
- Environmental: Assistive Technology
- Personal: Age & Gender
Image: Flow chart
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Slide 6
Source of data
- Pooled 3 years of HNIS data (1997, 1998, 1999)
- Sample: about 97,000 working-age adults (18-64 years)
- LFP, age, gender from family questionnaire
- Mobility limitation, assistive technology from sample adult questionnaire
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Slide 7
Methods
- Weighted and adjusted estimates were calculated using Stata 6.0
- Descriptive statistics (cross tabs) predict AT Use and Labor Force Participation (LFP)
- Multivariate logistic regression was also used to predict LFP
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Slide 8
Questions for mobility categories
- By yourself and without using any special equipment, how difficult is it for you to...:
- Walk 1/4 of a mile (about 3 city blocks)?
- Walk up 10 steps without resting?
- Stand or be on your feet for about 2 hours?
- Is it not at all difficult (O), only a little difficult (1), somewhat difficult (2), very difficult (3), or can't you do it at all (4)?
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Slide 9
Mobility severity categories
(summed across walk, climb stairs, stand)
| Mobility Severity |
Score range |
Number in sample |
Percent (weighted) |
| None or mild |
0-3 |
73,462 |
93.09% |
| Moderate |
4-9 |
4,668 |
5.19% |
| Severe |
10-12 |
1,618 |
1.72% |
| Score range:
| 0 = no difficulty walk, climb, stand |
| 12 = unable to walk, climb or stand |
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Slide 10
Labor force participation
- In the labor force:
- Working at job or business for pay
- Looking for work
- Temporarily laid off
- Reasons why not in labor force:
- Managing household
- Going to school
- Poor health
- Disability
- Retirement
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Slide 11
Assistive technology question
- "Do you now have a health problem that requires you to use special equipment, such as a cane, a wheelchair, a special bed, or a special telephone?"
- Yes = AT User
- No = Nonuser
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Slide 12
Importance of learning more about this AT variable
- This is the single question about AT on the NHIS (apart from a question on hearing aids)
- Exact question used in all states on BRFSS, beginning 2001
- The NHIS and BRFSS AT question also used as an objective in Healthy People 2010
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Slide 13
These 1997-99 data compared to NHIS-D (1994-95)
Percent who use AT by age group and data source
| |
Ages |
| 18-44 |
45-64 |
Total:
18-64 |
NHIS 97-99
(1 question)
| 1.52% |
4.62% |
2.58% |
NHIS-D 94-95
(multiple Q's)
| 2.91% |
7.09% |
4.25% |
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Slide 14
As expected, mobility severity related to AT Use
Percent using AT, by mobility limitation, gender & age
| Men |
Mobility |
| None/mild |
Moderate |
Severe |
| 18-44 years |
0.9% |
22.5% |
70.3% |
| 45-64 years |
1.1% |
24.5% |
61.9% |
| Total: 18-64 |
1.0% |
23.7% |
64.3% |
| Women |
|
| 18-44 years |
0.5% |
9.8% |
48.1% |
| 45-64 years |
0.9% |
14.4% |
52.2% |
| Total: 18-64 |
0.6% |
12.5% |
51.1% |
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Slide 15
No surprise: mobility severity negatively related to LFP
Percent in labor force, by mobility limitation, gender & age
| Men |
Mobility |
| None/mild |
Moderate |
Severe |
| 18-44 years |
85.0% |
55.9% |
33.2% |
| 45-64 years |
81.2% |
42.5% |
22.7% |
| Total: 18-64 |
83.8% |
47.6% |
25.8% |
| Women |
|
| 18-44 years |
73.4% |
53.7% |
35.1% |
| 45-64 years |
70.0% |
43.3% |
24.8% |
| Total: 18-64 |
72.3% |
47.5% |
27.5% |
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Slide 16
More surprising: AT use negatively related to LFP (men)
For men, percent in labor force, by AT use, mobility & age
| No AT Use |
Age |
Mobility |
| None/mild |
Moderate |
Severe |
| 18-44 years |
85.1% |
59.8% |
29.4% |
| 45-64 years |
81.3% |
45.0% |
27.8% |
| Total: 18-64 |
83.9% |
50.8% |
28.2% |
| AT Use |
|
|
| 18-44 years |
79.7% |
42.4% |
34.8% |
| 45-64 years |
77.2% |
34.5% |
19.5% |
| Total: 18-64 |
78.8% |
37.4% |
24.4% |
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Slide 17
AT use also negatively related to LFP for women
For women, percent in labor force, by AT use, mobility & age
| No AT Use |
Age |
Mobility |
| None/mild |
Moderate |
Severe |
| 18-44 years |
73.4% |
54.3% |
29.1% |
| 45-64 years |
70.1% |
45.2% |
26.9% |
| Total: 18-64 |
72.3% |
49.0% |
27.5% |
| AT Use |
|
|
| 18-44 years |
74.6% |
47.8% |
41.7% |
| 45-64 years |
59.5% |
32.6% |
23.0% |
| Total: 18-64 |
67.6% |
37.4% |
40.4% |
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Slide 18
Why might people who use AT have lower LFP? -1
- AT use might be functioning as a "severity" marker, even within the mobility severity categories.
- Among those with mobility limitations, people using AT may have other limitations (e.g. sensory)
- Additional analysis needed to answer those questions
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Slide 19
Why might people who use AT have lower LFP? -2
- People whose condition "requires them to use AT" (the AT users in this survey) might not have access to the most appropriate AT that would facilitate their participation in work or other activities.
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Slide 20
Workplace accommodations not specifically measured in NHIS
- Urban Institute found that 7% of non-workers with disabilities needed special equipment to facilitate working (NHIS-D)
- Special office equipment
- Braille, large print, special lighting
- Voice synthesizer, TDD, other technical devices
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Slide 21
Of course, more complex ICF models include more variables
- Level I: Health Factors
- Level II:
- Body Structure & Function
- Activity: Mobility
- Participation: Labor Force
- Level III:
- Environmental: SSI/SSDI
- Environmental: AT/PAS
- Personal: Age & Gender
Image: Flow chart
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Slide 22
Complex model: AT/PAS related to higher LFP for some groups
- Among people who received SSI/SSDI, odds of working are higher for those who also use AT and/or PAS
- Fits with Social Security Administration (SSA) finding: beneficiaries who received accommodations upon return to work rated AT and PAS as most helpful for job retention
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Slide 23
Summary
- Power of aggregating data sets across years to study small samples
- Better understanding of properties of NHIS AT variable contributes to aother analysis, including BRFSS & Healthy People 2010 objectives
- Utility of ICF for classifying variables, planning analysis, understanding results
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Slide 24
Directions for future research
- Single NHIS AT question important and useful, but not sufficient for understanding AT impact
- Other surveys (in addition to NHIS) need for specific AT & relationship to work and other social participation
- NHIS could be used to track changes in AT over time if a useful, short set of AT questions developed.
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