BACKGROUND AND PURPOSE: The purpose of this study was to evaluate stroke patient-proxy agreement with respect to social determinants of health, including depression, optimism, and spirituality, and to explore approaches to minimize proxy-introduced bias. METHODS: Stroke patient-proxy pairs from the Brain Attack Surveillance in Corpus Christi Project were interviewed (n=34). Evaluation of agreement between patient-proxy pairs included calculation of intraclass correlation coefficients, linear regression models (ProxyResponse=alpha(0)+alpha(1)PatientResponse+delta, where alpha(0)=0 and alpha(1)=1 denotes no bias) and kappa statistics. Bias introduced by proxies was quantified with simulation studies. In the simulated data, we applied 4 approaches to estimate regression coefficients of stroke outcome social determinants of health associations when only proxy data were available for some patients: (1) substituting proxy responses in place of patient responses; (2) including an indicator variable for proxy use; (3) using regression calibration with external validation; and (4) internal validation. RESULTS: Agreement was fair for depression (intraclass correlation coefficient, 0.41) and optimism (intraclass correlation coefficient, 0.48) and moderate for spirituality (kappa, 0.48 to 0.53). Responses of proxies were a biased measure of the patients' responses for depression, with alpha(0)=4.88 (CI, 2.24 to 7.52) and alpha(1)=0.39 (CI, 0.09 to 0.69), and for optimism, with alpha(0)=3.82 (CI, -1.04 to 8.69) and alpha(1)=0.81 (CI, 0.41 to 1.22). Regression calibration with internal validation was the most accurate method to correct for proxy-induced bias. CONCLUSIONS: Fair/moderate patient-proxy agreement was observed for social determinants of health. Stroke researchers who plan to study social determinants of health may consider performing validation studies so corrections for proxy use can be made.
BACKGROUND AND PURPOSE: The purpose of this study was to evaluate strokepatient-proxy agreement with respect to social determinants of health, including depression, optimism, and spirituality, and to explore approaches to minimize proxy-introduced bias. METHODS:Strokepatient-proxy pairs from the Brain Attack Surveillance in Corpus Christi Project were interviewed (n=34). Evaluation of agreement between patient-proxy pairs included calculation of intraclass correlation coefficients, linear regression models (ProxyResponse=alpha(0)+alpha(1)PatientResponse+delta, where alpha(0)=0 and alpha(1)=1 denotes no bias) and kappa statistics. Bias introduced by proxies was quantified with simulation studies. In the simulated data, we applied 4 approaches to estimate regression coefficients of stroke outcome social determinants of health associations when only proxy data were available for some patients: (1) substituting proxy responses in place of patient responses; (2) including an indicator variable for proxy use; (3) using regression calibration with external validation; and (4) internal validation. RESULTS: Agreement was fair for depression (intraclass correlation coefficient, 0.41) and optimism (intraclass correlation coefficient, 0.48) and moderate for spirituality (kappa, 0.48 to 0.53). Responses of proxies were a biased measure of the patients' responses for depression, with alpha(0)=4.88 (CI, 2.24 to 7.52) and alpha(1)=0.39 (CI, 0.09 to 0.69), and for optimism, with alpha(0)=3.82 (CI, -1.04 to 8.69) and alpha(1)=0.81 (CI, 0.41 to 1.22). Regression calibration with internal validation was the most accurate method to correct for proxy-induced bias. CONCLUSIONS: Fair/moderate patient-proxy agreement was observed for social determinants of health. Stroke researchers who plan to study social determinants of health may consider performing validation studies so corrections for proxy use can be made.
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