Psychometric and clinical validity of the SF-36 General Health Survey in the Whitehall II Study (original) (raw)
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Arthritis Care & Research, 2011
The SF-36 (also known as the Medical Outcomes Study 36-Item Short Form Health Survey) and SF-12 are multi-item generic health surveys intended to measure "general health concepts not specific to any age, disease, or treatment group" (p.474 1). The SF-12 is a shorter version of the SF-36 that uses only 12 questions to measure functional health and well-being from the patient's perspective. The original objective was to develop a short generic health status measure that reproduces the two summary scores of the SF-36-the Physical Component Summary (PCS) score and Mental Component Summary (MCS) score 2. The SF-36 and SF-12 are suitable for use in general as well as clinical populations and as such, can be used to compare health between populations and between diseases. The SF-36 and the SF-12 Health Surveys are available in original and revised versions. The SF-36 and SF-12 were was first published in 1992 and 1996, respectively, with the revised versions of both questionnaires published in 2000. The revised versions are very similar to their original forms, with major differences involving changes in item wording, revision of the response scale to incorporate greater number of response options, and norm-based scoring 3 .
Quality of Life Research an International Journal of Quality of Life Aspects of Treatment Care and Rehabilitation, 2005
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Quality of Life Research, 2005
General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research-You may not further distribute the material or use it for any profit-making activity or commercial gain-You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Assessing the validity of the SF-36 General Health Survey
Quality of Life Research, 1997
Our objective was to assess the validity of the SF-36 General Health Survey against the Social Maladjustment Schedule (SMS) and two questionnaire measures, the Social Problem Questionnaire and the Nottingham Health Profile (NHP) in a random subsample of 206 men and women from the Whitehall II study, a longitudinal survey of health and disease amongst 10,308 London-based civil servants. We found that social functioning on the SF-36 correlated significantly with social contacts, total satisfaction and total management scores on the SMS, and social isolation and emotional reactions on the NHP. General mental health on the SF-36 was associated with marriage, social contacts, leisure scores, total satisfaction and total management scores on the SMS, and emotional reactions, energy level and social isolation on the NHP. Conversely, physical functioning and physical role limitations were generally not associated with the SMS but were associated with physical abilities and pain on the NHP. In conclusion, this study offers evidence of the discriminant validity of the general mental health and physical functioning scales of the SF-36. We also found moderate construct and criterion validity for the social functioning scale of the SF-36 and considerable overlap between the general mental health and social functioning scales.
Developing summary scores of health-related quality of life for a population-based survey
Public Health …, 2009
Objective. Health-related quality of life (HRQOL) is an important indicator of public health. The Centers for Disease Control and Prevention's (CDC's) Behavioral Risk Factor Surveillance System (BRFSS) includes nine HRQOL items that can be used to monitor the health status of the nation. The objective of this study was to examine the numerical relationships among these HRQOL items to develop summary scores by combining items. Methods. Using 2001 and 2002 BRFSS data from states that included all nine HRQOL questions, factor analyses were performed to determine whether the items would group together into multi-item scales. Results. Two factors emerged, corresponding conceptually to a physical health construct and a mental health construct. The resulting scales demonstrated acceptable internal consistency and ability to distinguish between population subgroups known to differ on HRQOL. Conclusions. This study provides support for condensing the BRFSS core and optional HRQOL questions into two scales. These scales provide more complete information about physical and mental HRQOL than is available from single items, while limiting the number of individual variables required for a given analysis. However, the four core HRQOL questions focus primarily on physical health. Thus, the five supplemental questions should be included when measuring mental health is of interest.
2017
The 15D is a generic, 15-dimensional, standardised, self-administered measure of HRQOL, that can be used both as a profile and as a single index score measure. This paper examines the acceptability, reliability, validity and sensitivity of two versions (15D.1 and 15D.2) of its health state descriptive system as a profile measure compared with the Nottingham Health Profile (NHP), SF-20 and EuroQol by using several data sets and methods. The response and completion rates show that the acceptability is comparable to NHP, SF-20 and EuroQol. Reliability in terms of repeatability is high, even higher than for NHP. There is substantial evidence of content and construct validity (cross-sectional and longitudinal) and depression-related criterion validity. On roughly comparable dimensions the discriminatory power of 15D.1 appears to be superior to NHP, at least equivalent to SF-20, that of 15D.2 superior to EuroQol and 15D.1, and the responsiveness of 15D.1 to change seems to be similar to N...
Quality of Life Research, 2011
Purpose This study proposes to identify for 5 widely used generic HRQL and QOL measures the extent to which function and global feelings of well-being are represented in their content. Methods The 5 indices were the EQ-5D, the HUI, the SF-36, SF-12, and the WHOQOL-Bref. A total of 15 raters with a variety of health and research backgrounds mapped the items. Raters independently identified all codes that could possibly map to the item and indicated the code that best reflected the underlying intent of the item, using the standardized mapping rules and methodology. A Delphi process aided consensus for each of the items. The consensus rounds involved reconsideration of item codes for which 70% of raters did not agree on the ''best'' code. These consensus rounds were terminated when item codes reached the threshold of 70% agreement or when it became evident from that consensus would not be reached. Results Function was a predominant construct for the 5 indices, with the proportion of items capturing function ranging from a low of 27% for the WHOQOL-Bref to a high of 92% for the SF-12. Less than 50% of items within the indices mapped to the granularity of function as described by the ICF. Conclusions This paper demonstrates an additional method to validate the content of health-related indices to supplement the qualitative methods of consulting with experts and patients.
Quality of Life Research, 2010
Purpose To compare the relationship of the eight SF-36 v1 subscale scores to the summary scores of the PCS and MCS derived from two different scoring algorithms: one based on the original scoring method (Ware, Kosinski and Keller, SF-36 physical and mental health summary scales: a users manual. The Health Institute, New England Medical Centre, Boston, MA, 1994); and the other based on scoring algorithms that use parameters derived from structural equation modelling. Further, to provide SF-12 scoring algorithms similarly based on structural equation modelling. Methods The Australian Bureau of Statistics 1995 Australian National Health Survey dataset was used as the basis for the production of coefficients. There were 18,141 observations with no missing data for all eight SF-36 subscales following imputation of data items, and 17,479 observations with no missing data for the SF-12 data items. Data were analysed in LISREL V8.71. Structural equation models were fit to the data in confirmatory factor analyses producing weighted least squares estimates, which overcame anomalies found in the traditional orthogonal scoring methods. Results Models with acceptable fits to the hypothesised factor structure were produced, generating factor score weighting coefficients for use with the SF-36 and SF-12 data items, to produce PCS and MCS summary scores consistent with their underlying subscale scores. Conclusions The coefficients generated will score the SF-36 summary PCS and MCS in a manner consistent with their subscales. Previous Australian studies using version 1 of SF-36 or SF-12 can re-score their summary scores using these coefficients.
The SF-36 scales are not accurately summarised by independent physical and mental component scores
Quality of Life Research, 2008
Objectives The Short Form 36 Health Status Questionnaire (SF-36) has eight scales that can be condensed into two components: physical component summary (PCS) and mental component summary (MCS). This paper investigates: (1) the assumption that PCS and MCS are orthogonal, (2) the applicability of a single model to different condition-specific subgroups, and (3) a reduced fivescale model. Study design and setting We performed a secondary analysis of two large-scale data sets that utilised the SF-36: the Health Survey for England 1996 and the Welsh Health Survey 1998. We used confirmatory factor analysis to compare hypothetical orthogonal and oblique factor models, and exploratory factor analysis to derive data-driven models for condition-specific subgroups. Results Oblique models gave the best fit to the data and indicated a considerable correlation between PCS and MCS. The loadings of the eight scales on the two component summaries varied significantly by disease condition. The choice of model made an important difference to norm-referenced scores for large minorities, particularly patients with a mental illness or mentalphysical comorbidity. Conclusions We recommend that users of the SF-36 adopt the oblique model for calculating PCS and MCS. An oblique five-scale model provides a more universal factor structure without loss of predictive power or reliability.