Dataset Information

A survey dataset on determinants of administrative corruption.

ABSTRACT: This data article describes a survey dataset on administrative corruption and its main determinants (culture, organizational culture, political instability, and institutional weakness) in addition to social class. Prior research was consulted to determine indicators of the constructs of administrative corruption. Each construct has four reflective indicators while social class has formative variables. All items are measured using a seven-point Likert scale and semantic differential scale types. Through Google Form, I collected 677 responses that reflect the perspective of the general public in Basra, Iraq. The paper shows how to build observed indicators for administrative corruption and its main causes, and a summary of the raw data. The dataset can be reused by other researchers and easily downloaded from the Mendeley Data repository (https://doi.org/10.17632/xh22fsmvmc.2). While the dataset is prepared for building and testing a model using a structural equation modeling approach, it sheds light on the debate regarding an increasingly important topic internationally, and especially in Middle Eastern countries, such as Iraq, that experience high rates of corruption and political instability.

SUBMITTER: Al-Jundi SA

PROVIDER: S-EPMC6889175 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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A survey dataset on determinants of administrative corruption.

Al-Jundi Salem A SA

Data in brief 20191116

This data article describes a survey dataset on administrative corruption and its main determinants (culture, organizational culture, political instability, and institutional weakness) in addition to social class. Prior research was consulted to determine indicators of the constructs of administrative corruption. Each construct has four reflective indicators while social class has formative variables. All items are measured using a seven-point Likert scale and semantic differential scale types. ...[more]

PMID: 31828186

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Project description:Between 2012 and 2017, N = 2814 youth between the ages of 4 and 20 were in child protective services (CPS) custody in Hamilton County, Ohio, and placed in out-of-home care. Child welfare administrative records were extracted and linked to electronic health records for all encounters at Cincinnati Children's Hospital Medical Center, with n = 2787 (99.1%) of records successfully linked prior to de-identifying the data for research purposes. Child welfare administrative data fields in the dataset include demographics, dates of entry into and exit from protective custody and out-of-home care, reasons for entry into custody, dates of placement changes, reasons for placement changes, and types of placement (e.g., foster home, kinship home, group home, residential treatment, independent living). Electronic health records (EHR) data fields include demographics, all inpatient and outpatient encounters with medications, diagnoses, screening results, laboratory test results, flowsheet data, and problem list entries. Data have been coded to capture broader categories of health needs and encounter details, medications, and other health concerns. Due to the high representation of children in CPS custody and out-of-home care who are also represented in the EHR data, this dataset provides a comprehensive view of the medical needs and health concerns for school-aged children in CPS custody in an entire county. As a result, these data can be useful for understanding the emergence of global and specific health concerns, frequency of healthcare use, and placement stability for all youth in CPS custody in this community, accounting for variation due to other health and child welfare factors. These data are likely generalizable to other mid-sized urban communities where academic medical centers provide healthcare for children in CPS custody. De-identified data may be made available to other researchers with approved data transfer agreements between academic institutions in place.

Project description:BackgroundLatin American countries are often limited in the availability of food outlet data. There is a need to use online search engines that allow the identification of food outlets and assess their agreement with field observations. We aimed to assess the agreement in the density of food outlets provided by a web collaborative data (Google) against the density obtained from an administrative registry. We also determined whether the agreement differed by type of food outlet and by area-level socioeconomic deprivation.MethodsIn this cross-sectional study, we analyzed 1,693 census tracts from the municipalities of Hermosillo, Leon, Oaxaca de Juarez, and Tlalpan. The Google service was used to develop a tool for the automatic acquisition of food outlet data. To assess agreement, we compared food outlet densities obtained with Google against those registered in the National Statistical Directory of Economic Units (DENUE). Continuous densities were assessed using Bland-Altman plots and concordance correlation coefficient (CCC), while agreement across tertiles of density was estimated using weighted kappa.ResultsThe CCC indicated a strong correlation between Google and DENUE in the overall sample (0.75); by food outlet, most of the correlations were from negligible (0.08) to moderate (0.58). The CCC showed a weaker correlation as deprivation increased. Weighted kappa indicated substantial agreement between Google and DENUE across all census tracts (0.64). By type of food outlet, the weighted kappa showed substantial agreement for restaurants (0.69) and specialty food stores (0.68); the agreement was moderate for convenience stores/small food retail stores (0.49) and fair for candy/ice cream stores (0.30). Weighted kappa indicated substantial agreement in low-deprivation areas (0.63); in very high-deprivation areas, the agreement was moderate (0.42).ConclusionsGoogle could be useful in assessing fixed food outlet densities as a categorical indicator, especially for some establishments, like specialty food stores and restaurants. The data could also be informative of the availability of fixed food outlets, particularly in less deprived areas.

Dataset Information

A survey dataset on determinants of administrative corruption.

Publications

A survey dataset on determinants of administrative corruption.

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