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Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

ABSTRACT: The structural equation modeling (SEM) approach for detection of response shift (Oort in Qual Life Res 14:587-598, 2005. doi: 10.1007/s11136-004-0830-y ) is especially suited for continuous data, e.g., questionnaire scales. The present objective is to explain how the SEM approach can be applied to discrete data and to illustrate response shift detection in items measuring health-related quality of life (HRQL) of cancer patients.The SEM approach for discrete data includes two stages: (1) establishing a model of underlying continuous variables that represent the observed discrete variables, (2) using these underlying continuous variables to establish a common factor model for the detection of response shift and to assess true change. The proposed SEM approach was illustrated with data of 485 cancer patients whose HRQL was measured with the SF-36, before and after start of antineoplastic treatment.Response shift effects were detected in items of the subscales mental health, physical functioning, role limitations due to physical health, and bodily pain. Recalibration response shifts indicated that patients experienced relatively fewer limitations with "bathing or dressing yourself" (effect size d = 0.51) and less "nervousness" (d = 0.30), but more "pain" (d = -0.23) and less "happiness" (d = -0.16) after antineoplastic treatment as compared to the other symptoms of the same subscale. Overall, patients' mental health improved, while their physical health, vitality, and social functioning deteriorated. No change was found for the other subscales of the SF-36.The proposed SEM approach to discrete data enables response shift detection at the item level. This will lead to a better understanding of the response shift phenomena at the item level and therefore enhances interpretation of change in the area of HRQL.

SUBMITTER: Verdam MG

PROVIDER: S-EPMC4870306 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

Verdam Mathilde G E MG Oort Frans J FJ Sprangers Mirjam A G MA

Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation 20151222 6

<h4>Purpose</h4>The structural equation modeling (SEM) approach for detection of response shift (Oort in Qual Life Res 14:587-598, 2005. doi: 10.1007/s11136-004-0830-y ) is especially suited for continuous data, e.g., questionnaire scales. The present objective is to explain how the SEM approach can be applied to discrete data and to illustrate response shift detection in items measuring health-related quality of life (HRQL) of cancer patients.<h4>Methods</h4>The SEM approach for discrete data i ...[more]

PMID: 26694962

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Project description:ObjectiveThe objective was to investigate interplay and physical and mental component scores between change (Δ) in health-related quality of life (HRQoL) quantified by the physical component score (PCS) and mental component score (MCS) retrieved from short-form health survey (SF-36), change in disease activity (ΔDAS28CRP) and manifestations of PsA.MethodsPsA patients initiating new medical therapy were enrolled. Independent disease measures evaluating disease activity, enthesitis, psoriasis, pain and fatigue were collected at treatment initiation and after 4 months. Interplay between independent disease measures and dependent outcome measures, ΔPCS and ΔMCS, was described with univariate regression analyses. Multivariate regression analyses were applied to assess the impact of independent variables, such as individual disease outcome measures vs ΔDAS28CRP on ΔPCS and ΔMCS.ResultsOne hundred and eight PsA patients were included. In the univariate regression analyses, improvement in fatigue, pain and disability were associated with improvement in ΔPCS (β; -2.08, -0.18 and -13.00, respectively; all P < 0.001) and ΔMCS (β; -1.59, -0.12 and -6.07, respectively; P < 0.001, P < 0.001 and P = 0.003, respectively). When patient-reported outcomes were included in the final multivariate models, improvements in ΔPCS and ΔMCS were associated with improvements in pain, fatigue and disability (P < 0.001). Improvement in enthesitis impacted ΔPCS positively (β -0.31, P < 0.001). No association was found between change in skin psoriasis, ΔPCS and ΔMCS (β 0.15, P = 0.056 and β 0.05, P = 0.561, respectively).ConclusionIn this PsA patient cohort, diminishing pain, disability and fatigue improved PCS and MCS significantly. Changes in enthesitis and psoriasis did not grossly impact HRQoL compared with DAS28CRP. Individual PsA manifestations influence HRQoL differently, which is important clinically when targeting treatment.Trial registrationClinicalTrials.gov, http://clinicaltrials.gov, NCT02572700.

Project description:ObjectiveThe purpose of this meta-analysis is to gather and investigate pooled information on the responsiveness of the main patient outcome measure in cardiac rehabilitation (CR) and pulmonary rehabilitation (PR). The main outcome measure in CR and PR has been found to be the Medical Outcomes Study Short Form-36 health survey (SF-36).Data sourcesA previous systematic effectiveness review of this literature was used as the basis of this statistical analysis, with the bulk of articles being observational studies.Study selectionThis meta-analysis assessed articles on CR that used SF-36 pre and post "within" (per interventional group) mean scores and in the PR literature that used the SF-36 and the Chronic Respiratory Questionnaire (CRQ) "within" change scores.Data extractionEach group of patients in the chosen literature were taken to represent a single group, so that studies such as randomized controlled trials were listed twice. We undertook a correlation analysis between SF-36 pre and post "within" mean scores in the CR literature. In the PR literature, we undertook a correlation analysis between SF-36 and the CRQ "within" change scores; this involved Spearman correlation coefficients.Data synthesisThe SF-36 Mental Composite Score domain is the most responsive of the composite SF-36 domains, with the Physical Composite Score showing less ability to discriminate in the higher SF-36 scores. In the individual domains, Role Emotional scored r=0.52, P≤.001 with only 27% of the variance explained, and Role Physical with r=0.49, P≤.005 had only 24% of the variance explained. In the PR literature Spearman rank correlation coefficient shows that SF-36 Physical Composite Score has a weaker correlation to the CRQ at 0.39 than the SF-36 Mental Composite Score, which was 0.63.ConclusionsThis suggests that the SF-36 is not suited as a pre- to postprogram assessment tool for CR and PR. More studies, however, need to be conducted particularly in CR with regard to the responsiveness of the SF-36.

Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a rare disease with a median survival of 3-5 years after diagnosis with limited treatment options. The aim of this study is to assess the psychometric characteristics of the Short Form 36 Health Status Questionnaire (SF-36) in IPF and to provide disease specific minimally important differences (MID).MethodsData source was the European IPF Registry (eurIPFreg). The psychometric properties of the SF-36 version 2 were evaluated based on objective clinical measures as well as subjective perception. We analysed acceptance, feasibility, discrimination ability, construct and criterion validity, responsiveness and test-retest-reliability. MIDs were estimated via distribution and anchor-based approaches.ResultsThe study population included 258 individuals (73.3% male; mean age 67.3 years, SD 10.7). Of them 75.2% (194 individuals) had no missing item. The distribution of several items was skewed, although floor effect was acceptable. Physical component score (PCS) correlated significantly and moderately with several anchors, whereas the correlations of mental component score (MCS) and anchors were only small. The tests showed mainly significant lower HRQL in individuals with long-term oxygen therapy. Analyses in stable individuals did not show significant changes of HRQL except for one dimension and anchor. Individuals with relevant changes of the health status based on the anchors had significant changes in all SF-36 dimensions and summary scales except for the dimension PAIN. PCS and MCS had mean MIDs of five and six, respectively. Mean MIDs of the dimensions ranged from seven to 21.ConclusionIt seems that the SF-36 is a valid instrument to measure HRQL in IPF and so can be used in RCTs or individual monitoring of disease. Nevertheless, the additional evaluation of longitudinal aspects and MIDs can be recommended to further analyse these factors. Our findings have a great potential impact on the evaluation of IPF patients.Trial registrationThe eurIPFreg and eurIPFbank are listed in https://clinicaltrials.gov ( NCT02951416 ).

Dataset Information

Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

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Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

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