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A blessing and a curse? Political institutions in the growth and decay of generalized trust: a cross-national panel analysis, 1980-2009.

ABSTRACT: Despite decades of research on social capital, studies that explore the relationship between political institutions and generalized trust-a key element of social capital-across time are sparse. To address this issue, we use various cross-national public-opinion data sets including the World Values Survey and employ pooled time-series OLS regression and fixed- and random-effects estimation techniques on an unbalanced panel of 74 countries and 248 observations spread over a 29-year time period. With these data and methods, we investigate the impact of five political-institutional factors-legal property rights, market regulations, labor market regulations, universality of socioeconomic provisions, and power-sharing capacity-on generalized trust. We find that generalized trust increases monotonically with the quality of property rights institutions, that labor market regulations increase generalized trust, and that power-sharing capacity of the state decreases generalized trust. While generalized trust increases as the government regulation of credit, business, and economic markets decreases and as the universality of socioeconomic provisions increases, both effects appear to be more sensitive to the countries included and the modeling techniques employed than the other political-institutional factors. In short, we find that political institutions simultaneously promote and undermine generalized trust.

SUBMITTER: Robbins BG

PROVIDER: S-EPMC3338835 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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A blessing and a curse? Political institutions in the growth and decay of generalized trust: a cross-national panel analysis, 1980-2009.

Robbins Blaine G BG

PloS one 20120425 4

Despite decades of research on social capital, studies that explore the relationship between political institutions and generalized trust-a key element of social capital-across time are sparse. To address this issue, we use various cross-national public-opinion data sets including the World Values Survey and employ pooled time-series OLS regression and fixed- and random-effects estimation techniques on an unbalanced panel of 74 countries and 248 observations spread over a 29-year time period. Wi ...[more]

PMID: 22558122

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Project description:ObjectiveSpecific factors affecting generalizability of clinical prediction models are poorly understood. Our main objective was to investigate how measurement indicator variables affect external validity in clinical prediction models for predicting onset of vasopressor therapy.DesignWe fit logistic regressions on retrospective cohorts to predict vasopressor onset using two classes of variables: seemingly objective clinical variables (vital signs and laboratory measurements) and more subjective variables denoting recency of measurements.SettingThree cohorts from two tertiary-care academic hospitals in geographically distinct regions, spanning general inpatient and critical care settings.PatientsEach cohort consisted of adult patients (age greater than or equal to 18 yr at time of hospitalization), with lengths of stay between 6 and 600 hours, and who did not receive vasopressors in the first 6 hours of hospitalization or ICU admission. Models were developed on each of the three derivation cohorts and validated internally on the derivation cohort and externally on the other two cohorts.InterventionsNone.Measurements and main resultsThe prevalence of vasopressors was 0.9% in the general inpatient cohort and 12.4% and 11.5% in the two critical care cohorts. Models utilizing both classes of variables performed the best in-sample, with C-statistics for predicting vasopressor onset in 4 hours of 0.862 (95% CI, 0.844-0.879), 0.822 (95% CI, 0.793-0.852), and 0.889 (95% CI, 0.880-0.898). Models solely using the subjective variables denoting measurement recency had poor external validity. However, these practice-driven variables helped adjust for differences between the two hospitals and led to more generalizable models using clinical variables.ConclusionsWe developed and externally validated models for predicting the onset of vasopressors. We found that practice-specific features denoting measurement recency improved local performance and also led to more generalizable models if they are adjusted for during model development but discarded at validation. The role of practice-specific features such as measurement indicators in clinical prediction modeling should be carefully considered if the goal is to develop generalizable models.

Dataset Information

A blessing and a curse? Political institutions in the growth and decay of generalized trust: a cross-national panel analysis, 1980-2009.

Publications

A blessing and a curse? Political institutions in the growth and decay of generalized trust: a cross-national panel analysis, 1980-2009.

Similar Datasets

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