Literature DB >> 14533743

Assessing comparability of dressing disability in different countries by response conversion.

S van Buuren1, S Eyres, A Tennant, M Hopman-Rock.   

Abstract

BACKGROUND: Comparability of health data is a major challenge within the context of the Health Monitoring Programme of the European Commission. A common problem in surveys is that many variations of essentially the same question exist.
METHODS: Response conversion is a new method for improving comparability by scaling the data onto a common scale. Comparisons between member states can then be made in terms of the common scale. A first step is the construction of a conversion key. This is a relatively complex activity, but needs to be done only once. The second step is the actual data transformation. This is simple, and can be repeatedly done on a routine basis as new information arrives. Construction of the key is only possible if enough overlapping information can be found.
RESULTS: The method is illustrated for dressing disability from five European countries. Differences occur between countries, between sexes and between age groups. These were similar in magnitude.
CONCLUSION: Response conversion is a new method for enhancing comparability among existing data. Conversion can only be done if a key is available. More work is needed to establish the technique. Future implications within the Health Monitoring Programme are discussed.

Mesh:

Year:  2003        PMID: 14533743     DOI: 10.1093/eurpub/13.suppl_1.15

Source DB:  PubMed          Journal:  Eur J Public Health        ISSN: 1101-1262            Impact factor:   3.367


  4 in total

1.  Cohort profile: The Dynamic Analyses to Optimize Ageing (DYNOPTA) project.

Authors:  Kaarin J Anstey; Julie E Byles; Mary A Luszcz; Paul Mitchell; David Steel; Heather Booth; Colette Browning; Peter Butterworth; Robert G Cumming; Judith Healy; Timothy D Windsor; Lesley Ross; Lauren Bartsch; Richard A Burns; Kim Kiely; Carole L Birrell; Gerald A Broe; Jonathan Shaw; Hal Kendig
Journal:  Int J Epidemiol       Date:  2009-01-17       Impact factor: 7.196

2.  Statistical approaches to harmonize data on cognitive measures in systematic reviews are rarely reported.

Authors:  Lauren E Griffith; Edwin van den Heuvel; Isabel Fortier; Nazmul Sohel; Scott M Hofer; Hélène Payette; Christina Wolfson; Sylvie Belleville; Meghan Kenny; Dany Doiron; Parminder Raina
Journal:  J Clin Epidemiol       Date:  2014-12-08       Impact factor: 6.437

3.  Data Harmonization in Aging Research: Not so Fast.

Authors:  Margaret Gatz; Chandra A Reynolds; Deborah Finkel; Chris J Hahn; Yan Zhou; Catalina Zavala
Journal:  Exp Aging Res       Date:  2015       Impact factor: 1.645

4.  Cross-diagnostic validity in a generic instrument: an example from the Functional Independence Measure in Scandinavia.

Authors:  A Lundgren-Nilsson; A Tennant; G Grimby; K S Sunnerhagen
Journal:  Health Qual Life Outcomes       Date:  2006-08-23       Impact factor: 3.186

  4 in total

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