Sally Baker
Manjula Marella
Co-authors: Alexandra Devine, Tanya Edmonds,
Beth Sprunt, Kathy Fotis and Jill Keeffe
Disability Inclusive Development – where’s the data?
• Achieving Article 32 of the UNCRPD is hampered by gaps in evidence.
• Challenges include:
– limited existing disability data;
– limited knowledge of how to include people with disability and their priorities across the program cycle; and
– lack of mechanisms to support design and measurement of effectiveness of disability inclusive development activities.
•
Australia (2009)
New Zealand (2006)
Vanuatu (2009)
Fed. St. Micronesia (2010)
Kiribati (2004-05)
Solomon Islands (2004-05)
New Caledonia (-)
Tonga (2006)
Tuvalu (-)
Cook Islands (2012)
Nauru (2008)
Fiji (2008-09)
Samoa (2006)
0%
1,9
1,7
1,5
1,4
1,2
2,9
2,9
2,8
4,1
5%
11,0
12,0
10%
16,6
15%
18,5
Source: UNESCAP (2012) Disability at a Glance. Based on data submitted by governments.
20%
• Samoa Census 2006: 1.2%
• Vanuatu Census 2009: 12%
• The Washington Group questions:
– enable capture of disability prevalence data at the population level.
– Can be used to understand how particular issues are experienced by people with disability at the population level, e.g.:
• Health issues
• Education levels
• Poverty
But how can organisations design development programs which meet the priorities of people with disability at the local level?
• A tool was needed that could:
– Identify people with disability,
– Determine quality of life, and
– Determine barriers which impede access to the community.
• This data could be used by development organisations:
– As baseline data,
– To inform the design of disability inclusive development programs, and
– to contribute to evaluation.
• Review and analysis of existing tools, including the Washington Group, ICF questions, WHOQOL,
Kessler scale, PedsQL 4.0 and UNICEF 10Q.
• Focus group discussions and in-depth interviews with people with disability in Bangladesh.
• Review of drafts of the tool by advisory committees in Bangladesh, Fiji and Australia.
• Validation in Bangladesh and Fiji.
• Participants in advisory committees in
Bangladesh, Fiji and
Australia.
• Employed as data collectors in Bangladesh and Fiji.
• 2 questionnaires
– Household questionnaire
– Individual questionnaire
• Demographic information
• Self-assessment of Functioning
• Rights awareness
• Well-being
• Access to the community
– Particular items were removed or rephrased after being found to be psychometrically invalid.
• 15 items related to 8 domains: vision, hearing, communication, mobility, fine motor skills, cognition, appearance and mental health.
• In the last 6 months, have you had difficulties seeing, even if wearing glasses?
– Yes/no
– How often?
• Some of the time
• Most of the time
• All of the time
• 16 items related to quality of life and activity limitation
In the last 6 months, how often has your opinion been counted in the family?
1. All of the time
2. Most of the time
3. Some of the time
4. Never
5. Don’t know/can’t remember
In the last 6 months, to what extent could you access
…… as much as you would have needed/liked?
Which of the following have limited your ability to …..?
• Lack of information about …. opportunities
• No …. facilities in the area
• Physical accessibility of ….. facilities
• Negative attitudes towards you
• Cost
• Difficulty getting to …. facilities from home
• Family has difficulty assisting you to participate in ….
Which of these has limited your participation in ….. the most?
• Health
• Family decision making
• Assistive devices
• Rehabilitation services
• Water and sanitation
• Social activities
• Religion
• Government and social welfare
• DPOs
• Education
• Disaster management
• To estimate the prevalence of disability and its impact in Bogra, Bangladesh, using the RAD questionnaire.
• Two-stage cluster random sampling
– Compact segment sampling
• 66 clusters
• Of 2315 adults living in 931 households, 1855
(80%) individuals were recruited.
• N=1855
• 195 (10.5%, 95% CI: 8.78, 12.24) participants reported difficulties with functioning.
• Prevalence of disability extrapolated to Bogra district: 8.91% (95%CI: 7.34, 10.58)
• Difficulties most frequently reported
– Seeing (5.5%)
– Hearing (2.7%)
– Mobility (2.3%)
• Psychological distress – 5.3%
Gender
Female
Male
Age (years)
18-24
25-34
35-44
45-54
≥55
Socio-economic status
Rich
Middle
Poor
Education
10 years or more
5-9 years
1-4 years
None
Occupation
Housewife/working
Not working
Prevalence (95% CI)
Sample (n = 1855)
Adjusted OR (95%CI)*
10.26 (8.23, 12.28)
10.88 (8.56, 13.20)
2.71 (0.97, 4.45)
4.99 (3.00, 6.98)
10.55 (7.08, 14.03)
13.45 (9.44, 17.47)
25.15 (20.66, 29.64)
8.17 (5.16, 11.19)
7.57 (5.46, 9.67)
14.59 (11.58, 17.60)
6.48 (3.52, 9.45)
6.80 (4.56, 9.05)
11.29 (8.02, 14.56)
14.58 (11.61, 17.55)
8.70 (6.83, 10.56)
39.84 (31.11, 48.57)
1
0.97 (0.48, 1.94)
1
2.04 (0.90, 4.67)
4.86 (2.17, 10.89)
6.49 (2.97, 14.19)
9.15 (4.11, 20.41)
1
1.15 (0.65, 2.05)
2.11 (1.25, 3.56)
1
1.08 (0.47, 2.45)
1.17 (0.50, 2.71)
1.00 (0.45, 2.25)
1
3.99 (2.19, 7.28)
• People with disability had poor well-being scores (0.69, SD 1.25 logits) compared to the controls (1.67, SD 1.24 logits), p<0.001.
• Also had poor access to community compared to the controls (p<0.01).
cc_N hs_N
WB_Poor
Unemployed
Female
Home maker
25-34 cc_nn
35-44 no
18-24 hs_Y
Disable
55+ cc_Y hs_nn wo_Y
WB_Good
Labour
-.4
-.2
0 .2
Dimension 1 ( 43 % )
.4
10+
Male
Professional
Farmer
.6
.8
• Poor socio-economic status, old age and unemployment were independent predictors of disability supporting the previously established evidence on the relationship between poverty and disability.
• Participation in the community is associated with gender and disability.
• Data from RAD survey was useful to assess disability in terms of activity limitation, participation restriction and the contextual factors.
• A manual was prepared to provide information on the principles of RAD and guide implementation of the RAD survey.
• A toolkit comprising questionnaires and the manual was launched last year.
• RAD-enquiries@unimelb.edu.au
• Further validation of children version of RAD
• Awareness of rights
• Further testing is needed to investigate
– Application of RAD in disability inclusive development programs
– Responsiveness of RAD to identify change in participation after an intervention
• Philippines
– W-DARE ADRA - to improve access to quality sexual and reproductive health (SRH) programs for women with disability in the Philippines.
• Fiji
– AQEP : To identify children with disabilities among those who are not attending school in the communities surrounding five inclusive education demonstration schools.
• India
– CBM India funded project in Andhra Pradesh and
Uttarakhand.
• Developing a RAD Consortium to share learnings from application of RAD in different settings
• Investing in software development to improve data entry and analysis and therefore improve usability of
RAD
• Investing in regional RAD trainers
• The research is funded by the Australian aid program through an Australian Development
Research Award.
• International Centre for Diarrhoeal Disease
Research, Bangladesh (icddr,b)
• The Pacific Eye Institute, Fiji