Literature DB >> 17268926

The SF36 Version 2: critical analyses of population weights, scoring algorithms and population norms.

Graeme Hawthorne1, Richard H Osborne, Anne Taylor, Jan Sansoni.   

Abstract

BACKGROUND: The SF36 Version 2 (SF36V2) is a revision of the SF36 Version 1, and is a widely used health status measure. It is important that guidelines for interpreting scores are available.
METHOD: A population sample of Australians (n = 3015) weighted to achieve representativeness was administered the SF36V2. Comparisons between published US weights and sample derived weights were made, and Australian population norms computed and presented. MAJOR
FINDINGS: Significant differences were observed on 7/8 scales and on the mental health summary scale. Possible causes of these findings may include different sampling and data collection procedures, demographic characteristics, differences in data collection time (1998 vs. 2004), differences in health status or differences in cultural perception of the meaning of health. Australian population norms by age cohort, gender and health status are reported by T-score as recommended by the instrument developers. Additionally, the proportions of cases within T-score deciles are presented and show there are important data distribution issues. PRINCIPAL
CONCLUSIONS: The procedures reported here may be used by other researchers where local effects are suspected. The population norms presented may be of interest. There are statistical artefacts associated with T-scores that have implications for how SF36V2 data are analysed and interpreted.

Mesh:

Year:  2007        PMID: 17268926     DOI: 10.1007/s11136-006-9154-4

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


  38 in total

1.  Developing methods for assessing quality of life in different cultural settings. The history of the WHOQOL instruments.

Authors:  Suzanne M Skevington; Norman Sartorius; Marianne Amir
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2.  US valuation of the EQ-5D health states: development and testing of the D1 valuation model.

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Journal:  Med Care       Date:  2005-03       Impact factor: 2.983

3.  [The version 2.0 of the SF-36 Health Survey: results of a population-representative study].

Authors:  Matthias Morfeld; Monika Bullinger; Juliane Nantke; Elmar Brähler
Journal:  Soz Praventivmed       Date:  2005

4.  Population norms and meaningful differences for the Assessment of Quality of Life (AQoL) measure.

Authors:  Graeme Hawthorne; Richard Osborne
Journal:  Aust N Z J Public Health       Date:  2005-04       Impact factor: 2.939

5.  Tests of data quality, scaling assumptions, and reliability of the Danish SF-36.

Authors:  J B Bjorner; M T Damsgaard; T Watt; M Groenvold
Journal:  J Clin Epidemiol       Date:  1998-11       Impact factor: 6.437

6.  An examination of self- and telephone-administered modes of administration for the Australian SF-36.

Authors:  J J Perkins; R W Sanson-Fisher
Journal:  J Clin Epidemiol       Date:  1998-11       Impact factor: 6.437

7.  Testing the equivalence of translations of widely used response choice labels: results from the IQOLA Project. International Quality of Life Assessment.

Authors:  S D Keller; J E Ware; B Gandek; N K Aaronson; J Alonso; G Apolone; J B Bjorner; J Brazier; M Bullinger; S Fukuhara; S Kaasa; A Leplège; R W Sanson-Fisher; M Sullivan; S Wood-Dauphinee
Journal:  J Clin Epidemiol       Date:  1998-11       Impact factor: 6.437

8.  Toward an operational definition of health.

Authors:  D L Patrick; J W Bush; M M Chen
Journal:  J Health Soc Behav       Date:  1973-03

Review 9.  Impact of hepatitis C on health related quality of life: a systematic review and quantitative assessment.

Authors:  Brennan M R Spiegel; Zobair M Younossi; Ron D Hays; Dennis Revicki; Sean Robbins; Fasiha Kanwal
Journal:  Hepatology       Date:  2005-04       Impact factor: 17.425

10.  Is the SF-36 suitable for assessing health status of older stroke patients?

Authors:  P G O'Mahony; H Rodgers; R G Thomson; R Dobson; O F James
Journal:  Age Ageing       Date:  1998-01       Impact factor: 10.668

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  82 in total

1.  New Australian population scoring coefficients for the old version of the SF-36 and SF-12 health status questionnaires.

Authors:  Graeme Tucker; Robert Adams; David Wilson
Journal:  Qual Life Res       Date:  2010-05-04       Impact factor: 4.147

2.  Do Portuguese and UK health state values differ across valuation methods?

Authors:  Lara N Ferreira; Pedro L Ferreira; Donna Rowen; John E Brazier
Journal:  Qual Life Res       Date:  2011-05       Impact factor: 4.147

3.  Patterns of prescription opioid abuse and comorbidity in an aging treatment population.

Authors:  Theodore J Cicero; Hilary L Surratt; Steven Kurtz; M S Ellis; James A Inciardi
Journal:  J Subst Abuse Treat       Date:  2011-08-09

4.  The case for using country-specific scoring coefficients for scoring the SF-12, with scoring implications for the SF-36.

Authors:  Graeme Tucker; Robert Adams; David Wilson
Journal:  Qual Life Res       Date:  2015-09-28       Impact factor: 4.147

5.  Association between single-nucleotide polymorphisms in growth factor genes and quality of life in men with prostate cancer and the general population.

Authors:  Kimberly E Alexander; Suzanne Chambers; Amanda B Spurdle; Jyotsna Batra; Felicity Lose; Tracy A O'Mara; Robert A Gardiner; Joanne F Aitken; Judith A Clements; Mary-Anne Kedda; Monika Janda
Journal:  Qual Life Res       Date:  2015-02-28       Impact factor: 4.147

6.  Change in carers' activities after the death of their partners.

Authors:  Lorna Rosenwax; Sarah Malajczuk; Marina Ciccarelli
Journal:  Support Care Cancer       Date:  2013-10-19       Impact factor: 3.603

7.  Trends in health-related quality of life and health service use associated with body mass index and comorbid major depression in South Australia, 1998-2008.

Authors:  Evan Atlantis; Robert D Goldney; Kerena A Eckert; Anne W Taylor
Journal:  Qual Life Res       Date:  2011-12-29       Impact factor: 4.147

8.  Perceived social isolation in a community sample: its prevalence and correlates with aspects of peoples' lives.

Authors:  Graeme Hawthorne
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2007-11-09       Impact factor: 4.328

9.  Automatic quality of life prediction using electronic medical records.

Authors:  Sergeui Pakhomov; Nilay Shah; Penny Hanson; Saranya Balasubramaniam; Steven A Smith; Steven Allan Smith
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

10.  Longitudinal analysis of relationships between social support and general health in an Australian population cohort of young women.

Authors:  Libby Holden; Christina Lee; Richard Hockey; Robert S Ware; Annette J Dobson
Journal:  Qual Life Res       Date:  2014-08-07       Impact factor: 4.147

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