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Developing and feasibility testing of data collection methods for an economic evaluation of a supported selfmanagement programme for adults with a learning disability and type 2 diabetes

Overview of attention for article published in Pilot and Feasibility Studies, April 2018
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Title
Developing and feasibility testing of data collection methods for an economic evaluation of a supported selfmanagement programme for adults with a learning disability and type 2 diabetes
Published in
Pilot and Feasibility Studies, April 2018
DOI 10.1186/s40814-018-0266-8
Pubmed ID
Authors

John L. O’Dwyer, Amy M. Russell, Louise D. Bryant, Rebecca E. A. Walwyn, Alexandra M. Wright-Hughes, Elizabeth H. Graham, Judy M. Wright, Shaista Meer, Jacqueline Birtwistle, Amanda J. Farrin, Allan O. House, Claire T. Hulme

Abstract

The challenges of conducting research with hard to reach vulnerable groups are particularly pertinent for people with learning disabilities. Data collection methods for previous cost and cost-effectiveness analyses of health and social care interventions targeting people with learning disabilities have relied on health care/health insurance records or data collection forms completed by the service provider rather than by people with learning disabilities themselves. This paper reports on the development and testing of data collection methods for an economic evaluation within a randomised controlled trial (RCT) for a supported self-management programme for people with mild/moderate learning disabilities and type 2 diabetes. A case finding study was conducted to identify types of health and social care use and data collection methods employed in previous studies with this population. Based on this evidence, resource use questionnaires for completion by GP staff and interviewer-administered participant questionnaires (covering a wider cost perspective and health-related quality of life) were tested within a feasibility RCT. Interviewer-administered questionnaires included the EQ-5D-3L (the NICE recommended measure for use in economic evaluation). Participants were adults > 18 years with a mild or moderate learning disability and type 2 diabetes, with mental capacity to give consent to research participation. Data collection for questionnaires completed by GP staff requesting data for the last 12 months proved time intensive and difficult. Whilst 82.3% (121/147) of questionnaires were returned, up to 17% of service use items were recorded as unknown. Subsequently, a shorter recall period (4 months) led to a higher return rate but with a higher rate of missing data. Missing data for interviewer-administered participant questionnaires was > 8% but the interviewers reported difficulty with participant recall. Almost 60% (48/80) of participants had difficulty completing the EQ-5D-3L. Further investigation as to how service use can be recorded is recommended. Concerns about the reliability of identifying service use data directly from participants with a learning disability due to challenges in completion, specifically around recall, remain. The degree of difficulty to complete EQ-5D-3L indicates concerns regarding the appropriateness of using this measure in its current form in research with this population. Current Controlled Trials ISRCTN41897033 (registered 21 January 2013).

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 19%
Researcher 3 6%
Lecturer 3 6%
Student > Bachelor 3 6%
Librarian 2 4%
Other 10 21%
Unknown 18 38%
Readers by discipline Count As %
Medicine and Dentistry 6 13%
Nursing and Health Professions 4 8%
Psychology 4 8%
Social Sciences 4 8%
Economics, Econometrics and Finance 2 4%
Other 8 17%
Unknown 20 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 May 2018.
All research outputs
#15,508,366
of 23,047,237 outputs
Outputs from Pilot and Feasibility Studies
#733
of 1,047 outputs
Outputs of similar age
#208,097
of 326,560 outputs
Outputs of similar age from Pilot and Feasibility Studies
#20
of 23 outputs
Altmetric has tracked 23,047,237 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,047 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,560 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.