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Evaluation of smoking-specific and generic quality of life measures in current and former smokers in Germany and the United States.

Ware JE, Gandek B, Kulasekaran A, Guyer R - Health Qual Life Outcomes (2015)

Bottom Line: For purposes of evaluation, cross-sectional data were analyzed for two independent samples.Cross-sectional tests, including correlations with four biomarkers, support the validity of the new smoking-specific measures for use in studies of otherwise healthy smokers.Smoking-specific measures consistently performed better than generic QOL measures in all tests of validity.

View Article: PubMed Central - PubMed

Affiliation: John Ware Research Group, 10 Wheeler Court, Watertown, MA, 02472, USA. john.ware@jwrginc.com.

ABSTRACT

Background: Health-related quality of life (QOL) surveys include generic measures that enable comparisons across conditions and measures that focus more specifically on one disease or condition. We evaluated the psychometric properties of German- and English-language versions of survey scales representing both types of measures in samples of current and former smokers.

Methods: TQOLIT(™)v1 integrates new measures of smoking-specific symptoms and QOL impact attributed to smoking with generic SF-36 Health Survey measures. For purposes of evaluation, cross-sectional data were analyzed for two independent samples. Disease-free (otherwise healthy) adults ages 23-55 used a tablet to complete surveys in a clinical trial in Germany (125 current and 54 former smokers). Online general population surveys were completed in the US by otherwise healthy current and former smokers (N = 149 and 110, respectively). Evaluations included psychometric tests of assumptions underlying scale construction and scoring, score distributions, and reliability. Tests of validity included cross-sectional correlations and analyses of variance based on a conceptual framework and hypotheses for groups differing in self-reported smoking behavior (current versus former smoker, cigarettes per day (CPD)) and severity of smoking symptoms in both samples and, in the German trial only, clinical parameters of biomarkers of exposure.

Results: Tests of scaling assumptions and internal consistency reliability (alpha = 0.71-0.79) of the smoking-specific measures were satisfactory, although ceiling effects attenuated correlations for former smokers in both samples. Correlational evidence supporting validity of smoking-specific symptom and impact measures included their substantial inter-correlation and higher correlations (than generic measures) with smoking behavior (favoring former over current groups) and CPD in both samples. In the German trial, both smoking-specific measures correlated significantly (p < 0.05) with all four biomarkers. QOL impact attributed to smoking correlated with the SF-36 mental but not physical summary measures in both samples.

Conclusions: German- and English-language TQOLITv1 surveys have comparable and satisfactory psychometric properties. Cross-sectional tests, including correlations with four biomarkers, support the validity of the new smoking-specific measures for use in studies of otherwise healthy smokers. Smoking-specific measures consistently performed better than generic QOL measures in all tests of validity.

No MeSH data available.


Related in: MedlinePlus

Conceptual framework for smoking-specific and generic endpoints
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Fig1: Conceptual framework for smoking-specific and generic endpoints

Mentions: A conceptual framework or endpoint model is the basis for developing and evaluating evidence of validity for self-report measures of health outcomes [4]. The smoking-specific framework underlying hypotheses about results from tests of validity identifies relationships between variables (measures), along a continuum ranging from self-reported smoking behavior to the most generic health and well-being outcomes (Fig. 1). Applied to the current study of smoking behavior and QOL outcomes, this framework makes an important distinction between tests in relation to objectively-measured clinical parameters such as biomarkers of smoking exposure (box 1) and the hypothesized sequence of self-reported outcomes including smoking-specific symptoms (box 2) and the QOL impact attributed specifically to smoking (box 3). Among the hypothesized advantages of smoking-specific attributions for outcomes is greater validity than measures with attributions to health in general (box 4), in relation to both the amount and effects of smoking. An advantage of generic outcome measures is their usefulness in comparing outcomes across diseases and treatment interventions [6, 19]. We report here the first studies of whether QOL measures with attributions to smoking, as opposed to health in general, perform differently in tests of empirical validity.Fig. 1


Evaluation of smoking-specific and generic quality of life measures in current and former smokers in Germany and the United States.

Ware JE, Gandek B, Kulasekaran A, Guyer R - Health Qual Life Outcomes (2015)

Conceptual framework for smoking-specific and generic endpoints
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4537546&req=5

Fig1: Conceptual framework for smoking-specific and generic endpoints
Mentions: A conceptual framework or endpoint model is the basis for developing and evaluating evidence of validity for self-report measures of health outcomes [4]. The smoking-specific framework underlying hypotheses about results from tests of validity identifies relationships between variables (measures), along a continuum ranging from self-reported smoking behavior to the most generic health and well-being outcomes (Fig. 1). Applied to the current study of smoking behavior and QOL outcomes, this framework makes an important distinction between tests in relation to objectively-measured clinical parameters such as biomarkers of smoking exposure (box 1) and the hypothesized sequence of self-reported outcomes including smoking-specific symptoms (box 2) and the QOL impact attributed specifically to smoking (box 3). Among the hypothesized advantages of smoking-specific attributions for outcomes is greater validity than measures with attributions to health in general (box 4), in relation to both the amount and effects of smoking. An advantage of generic outcome measures is their usefulness in comparing outcomes across diseases and treatment interventions [6, 19]. We report here the first studies of whether QOL measures with attributions to smoking, as opposed to health in general, perform differently in tests of empirical validity.Fig. 1

Bottom Line: For purposes of evaluation, cross-sectional data were analyzed for two independent samples.Cross-sectional tests, including correlations with four biomarkers, support the validity of the new smoking-specific measures for use in studies of otherwise healthy smokers.Smoking-specific measures consistently performed better than generic QOL measures in all tests of validity.

View Article: PubMed Central - PubMed

Affiliation: John Ware Research Group, 10 Wheeler Court, Watertown, MA, 02472, USA. john.ware@jwrginc.com.

ABSTRACT

Background: Health-related quality of life (QOL) surveys include generic measures that enable comparisons across conditions and measures that focus more specifically on one disease or condition. We evaluated the psychometric properties of German- and English-language versions of survey scales representing both types of measures in samples of current and former smokers.

Methods: TQOLIT(™)v1 integrates new measures of smoking-specific symptoms and QOL impact attributed to smoking with generic SF-36 Health Survey measures. For purposes of evaluation, cross-sectional data were analyzed for two independent samples. Disease-free (otherwise healthy) adults ages 23-55 used a tablet to complete surveys in a clinical trial in Germany (125 current and 54 former smokers). Online general population surveys were completed in the US by otherwise healthy current and former smokers (N = 149 and 110, respectively). Evaluations included psychometric tests of assumptions underlying scale construction and scoring, score distributions, and reliability. Tests of validity included cross-sectional correlations and analyses of variance based on a conceptual framework and hypotheses for groups differing in self-reported smoking behavior (current versus former smoker, cigarettes per day (CPD)) and severity of smoking symptoms in both samples and, in the German trial only, clinical parameters of biomarkers of exposure.

Results: Tests of scaling assumptions and internal consistency reliability (alpha = 0.71-0.79) of the smoking-specific measures were satisfactory, although ceiling effects attenuated correlations for former smokers in both samples. Correlational evidence supporting validity of smoking-specific symptom and impact measures included their substantial inter-correlation and higher correlations (than generic measures) with smoking behavior (favoring former over current groups) and CPD in both samples. In the German trial, both smoking-specific measures correlated significantly (p < 0.05) with all four biomarkers. QOL impact attributed to smoking correlated with the SF-36 mental but not physical summary measures in both samples.

Conclusions: German- and English-language TQOLITv1 surveys have comparable and satisfactory psychometric properties. Cross-sectional tests, including correlations with four biomarkers, support the validity of the new smoking-specific measures for use in studies of otherwise healthy smokers. Smoking-specific measures consistently performed better than generic QOL measures in all tests of validity.

No MeSH data available.


Related in: MedlinePlus