Dataset Information

Using Anchoring Vignettes to Adjust Self-Reported Personality: A Comparison Between Countries.

ABSTRACT: Data from self-report tools cannot be readily compared between cultures due to culturally specific ways of using a response scale. As such, anchoring vignettes have been proposed as a suitable methodology for correcting against this difference. We developed anchoring vignettes for the Big Five Inventory-44 (BFI-44) to supplement its Likert-type response options. Based on two samples (Rwanda: n = 423; Philippines: n = 143), we evaluated the psychometric properties of the measure both before and after applying the anchoring vignette adjustment. Results show that adjusted scores had better measurement properties, including improved reliability and a more orthogonal correlational structure, relative to scores based on the original Likert scale. Correlations of the Big Five Personality Factors with life satisfaction were essentially unchanged after the vignette-adjustment while correlations with counterproductive were noticeably lower. Overall, these changed findings suggest that the use of anchoring vignette methodology improves the cross-cultural comparability of self-reported personality, a finding of potential interest to the field of global workforce research and development as well as educational policymakers.

SUBMITTER: Weiss S

PROVIDER: S-EPMC5861527 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Using Anchoring Vignettes to Adjust Self-Reported Personality: A Comparison Between Countries.

Weiss Selina S Roberts Richard D RD

Frontiers in psychology 20180314

Data from self-report tools cannot be readily compared between cultures due to culturally specific ways of using a response scale. As such, anchoring vignettes have been proposed as a suitable methodology for correcting against this difference. We developed anchoring vignettes for the Big Five Inventory-44 (BFI-44) to supplement its Likert-type response options. Based on two samples (Rwanda: <i>n</i> = 423; Philippines: <i>n</i> = 143), we evaluated the psychometric properties of the measure bot ...[more]

PMID: 29593621

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Project description:BackgroundAccurate estimates of hypertension prevalence are critical for assessment of population health and for planning and implementing prevention and health care programs. While self-reported data is often more economically feasible and readily available compared to clinically measured HBP, these reports may underestimate clinical prevalence to varying degrees. Understanding the accuracy of self-reported data and developing prediction models that correct for underreporting of hypertension in self-reported data can be critical tools in the development of more accurate population level estimates, and in planning population-based interventions to reduce the risk of, or more effectively treat, hypertension. This study examines the accuracy of self-reported survey data in describing prevalence of clinically measured hypertension in two racially and ethnically diverse urban samples, and evaluates a mechanism to correct self-reported data in order to more accurately reflect clinical hypertension prevalence.MethodsWe analyze data from the Detroit Healthy Environments Partnership (HEP) Survey conducted in 2002 and the National Health and Nutrition Examination (NHANES) 2001-2002 restricted to urban areas and participants 25 years and older. We re-calibrate measures of agreement within the HEP sample drawing upon parameter estimates derived from the NHANES urban sample, and assess the quality of the adjustment proposed within the HEP sample.ResultsBoth self-reported and clinically assessed prevalence of hypertension were higher in the HEP sample (29.7 and 40.1, respectively) compared to the NHANES urban sample (25.7 and 33.8, respectively). In both urban samples, self-reported and clinically assessed prevalence is higher than that reported in the full NHANES sample in the same year (22.9 and 30.4, respectively). Sensitivity, specificity and accuracy between clinical and self-reported hypertension prevalence were 'moderate to good' within the HEP sample and 'good to excellent' within the NHANES sample. Agreement between clinical and self-reported hypertension prevalence was 'moderate to good' within the HEP sample (kappa =0.65; 95% CI = 0.63-0.67), and 'good to excellent' within the NHANES sample (kappa = 0.75; 95%CI = 0.73-0.80). Application of a 'correction' rule based on prediction models for clinical hypertension using the national sample (NHANES) allowed us to re-calibrate sensitivity and specificity estimates for the HEP sample. The adjusted estimates of hypertension in the HEP sample based on two different correction models, 38.1% and 40.5%, were much closer to the observed hypertension prevalence of 40.1%.ConclusionsApplication of a simple prediction model derived from national NHANES data to self-reported data from the HEP (Detroit based) sample resulted in estimates that more closely approximated clinically measured hypertension prevalence in this urban community. Similar correction models may be useful in obtaining more accurate estimates of hypertension prevalence in other studies that rely on self-reported hypertension.

Project description:BackgroundConfigural, metric, and scalar measurement invariance have been indicators of bias-free statistical cross-group comparisons, although they are difficult to verify in the data. Low comparability of translated questionnaires or the different understanding of response formats by respondents might lead to rejection of measurement invariance and point to comparability bias in multi-language surveys. Anchoring vignettes have been proposed as a method to control for the different understanding of response categories by respondents (the latter is referred to as differential item functioning related to response categories or rating scales: RC-DIF). We evaluate the question whether the cross-cultural comparability of data can be assured by means of anchoring vignettes or by considering socio-demographic heterogeneity as an alternative approach.MethodsWe used the Health System Responsiveness (HSR) questionnaire and collected survey data in English (n = 183) and Arabic (n = 121) in a random sample of refugees in the third largest German federal state. We conducted multiple-group Confirmatory Factor Analyses (MGCFA) to analyse measurement invariance and compared the results when 1) using rescaled data on the basis of anchoring vignettes (non-parametric approach), 2) including information on RC-DIF from the analyses with anchoring vignettes as covariates (parametric approach) and 3) including socio-demographic covariates.ResultsFor the HSR, every level of measurement invariance between the Arabic and English languages was rejected. Implementing rescaling or modelling on the basis of anchoring vignettes provided superior results over the initial MGCFA analysis, since configural, metric and - for ordered categorical analyses-scalar invariance could not be rejected. A consideration of socio-demographic variables did not show such an improvement.ConclusionsSurveys may consider anchoring vignettes as a method to assess cross-cultural comparability of data, whereas socio-demographic variables cannot be used to improve data comparability as a standalone method. More research on the efficient implementation of anchoring vignettes and further development of methods to incorporate them when modelling measurement invariance is needed.

Dataset Information

Using Anchoring Vignettes to Adjust Self-Reported Personality: A Comparison Between Countries.

Publications

Using Anchoring Vignettes to Adjust Self-Reported Personality: A Comparison Between Countries.

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