scholarly journals ICT Adoption and the Digital Divide in Serbia: Factors and Policy Implications

10.28945/3247 ◽  
2008 ◽  
Author(s):  
Zlatko Kovacic ◽  
Dragan Vukmirovic
Keyword(s):  
Logistic Regression ◽  
Digital Divide ◽  
Predictive Accuracy ◽  
Classification Tree ◽  
Policy Implications ◽  
Individual Level ◽  
Internet Skills ◽  
Ict Adoption ◽  
Parsimonious Model ◽  
The Individual

This paper explores factors such as socio-demographics, income and wealth and e-skills that may influence the adoption of the ICTs at the individual level. We examine to what extent these factors contribute to the digital divide between different social groups in Serbia. We use the panel data from the survey “ICT usage in Republic of Serbia” in 2006 and 2007, covering over 3000 individuals/households, to perform a quantitative analysis of the digital divide and ICT adoption. Based on a classification tree and a logistic regression model, a profile of the typical ICT adopter and non-adopter is identified. The empirical results show the following: (i) the digital divide between age group 55-74 and those younger that 55 slightly increased in 2007 in case of regular Internet use; (ii) at the individual level the ICT adoption (use of PC, Internet and mobile phones) in Serbia is mainly influenced by the income and wealth of an individual, its computer and Internet skills and age; (iii) this result is quite robust across the methodological approaches used; and (iv) the classification tree approach is preferable since it gives the same predictive accuracy as the logistic regression with a more parsimonious model. The policy implications of these results are discussed.

scholarly journals Criminal Justice Debt During the Prisoner Reintegration Process: Who Has It and How Much?

2018 ◽  
Vol 46 (1) ◽  
pp. 154-172 ◽  
Author(s):  
Nathan W. Link
Keyword(s):  
Criminal Justice ◽  
Negative Binomial ◽  
Policy Implications ◽  
Community Supervision ◽  
Individual Level ◽  
Prisoner Reintegration ◽  
Negative Binomial Models ◽  
The Individual ◽  
Binomial Models ◽  
Transition Home

Much recent, national attention has centered on financial sanctions and associated debt burdens related to criminal justice. Scholars and practitioners alike have argued that financial debt among the incarcerated, in particular, exacerbates a transition home already defined by difficulties. This article takes a step back and assesses who is at risk of these adverse consequences in reentry by examining the extent of debt burdens that resulted from financial sanctions, its sources, and the individual-level factors that are associated with owing criminal justice debt. Relying on the Returning Home data ( N = 740), results from descriptive analyses, logistic regression, and negative binomial models show that a large proportion of respondents owed debts and that debt was strongly linked with being mandated to community supervision. In addition, debt amount was predicted by employment, income, and race. Policy implications in the realm of financial sanctioning by courts and correctional agencies are discussed.

scholarly journals Evaluation of Ocular Biomechanical Indices to Distinguish Normal from Keratoconus Eyes

2012 ◽  
Vol 1 (3) ◽  
pp. 145-150
Author(s):  
Bernardo Lopes ◽  
Allan Luz ◽  
Bruno Fontes ◽  
Isaac C Ramos ◽  
Fernando Correia ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Receiver Operating Characteristic ◽  
Linear Model ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Corneal Resistance Factor ◽  
Corneal Deformation ◽  
Eye Examination ◽  
The Individual

ABSTRACT Purpose To compare and assess the ability of pressure-derived parameters and corneal deformation waveform signal-derived parameters of the ocular response analyzer (ORA) measurement to distinguish between keratoconus and normal eyes, and to develop a combined parameter to optimize the diagnosis of keratoconus. Materials and methods One hundred and seventy-seven eyes (177 patients) with keratoconus (group KC) and 205 normal eyes (205 patients; group N) were included. One eye from each subject was randomly selected for analysis. Patients underwent a complete clinical eye examination, corneal topography (Humphrey ATLAS), tomography (Pentacam Oculus) and biomechanical evaluations (ORA Reichert). Differences in the distributions between the groups were assessed using the Mann- Whitney test. The receiver operating characteristic (ROC) curve was used to identify cutoff points that maximized sensitivity and specificity in discriminating keratoconus from normal corneas. Logistic regression was used to identify a combined linear model (Fisher 1.0). Results Significant differences in all studied parameters were detected (p < 0.05), except for W2. For the corneal resistance factor (CRF): Area under the ROC curve (AUROC) 89.1%, sensitivity 81.36%, specificity 84.88%. For the p1area: AUROC 91.5%, sensitivity 87.1%, specificity 81.95%. Of the individual parameters, the highest predictive accuracy was for the Fisher 1.0, which represents the combination of all parameters (AUROC 95.5%, sensitivity 88.14%, specificity 93.17%). Conclusion Waveform-derived ORA parameters displayed greater accuracy than pressure-derived parameters for identifying keratoconus. Corneal hysteresis (CH) and CRF, a diagnostic linear model that combines different parameters, provided the greatest accuracy for differentiating keratoconus from normal corneas. How to cite this article Luz A, Fontes B, Ramos IC, Lopes B, Correia F, Schor P, Ambrósio R. Evaluation of Ocular Biomechanical Indices to Distinguish Normal from Keratoconus Eyes. Int J Kerat Ect Cor Dis 2012;1(3):145-150.

Examining the Impact of Individual, Community, and Market Factors on Methamphetamine Use: A Tale of Two Cities

2005 ◽  
Vol 35 (4) ◽  
pp. 665-693 ◽  
Author(s):  
Nancy Rodriguez ◽  
Charles Katz ◽  
Vincent J. Webb ◽  
David R. Schaefer
Keyword(s):  
Drug Market ◽  
Community Level ◽  
Policy Implications ◽  
Individual Level ◽  
Methamphetamine Use ◽  
Level Data ◽  
Two Cities ◽  
Market Factors ◽  
The Individual ◽  
The Impact

Although prior studies have monitored the trends in methamphetamine use and reported its increase over the years, few studies have considered how community-level characteristics affect the use of methamphetamine. In this study, we utilize data from the Arrestee Drug Abuse Monitoring (ADAM) program from two cities to examine how individual-level, community-level, and drug market factors influence methamphetamine use. Results indicate that both individual and community-level data significantly influence methamphetamine use. Also, findings show that predictors of methamphetamine use (at the individual and community-level) differ significantly from marijuana, cocaine, and opiate use. Policy implications regarding law enforcement suppression and the treatment of methamphetamine users are discussed.

scholarly journals Title: Determinants of Minimum Acceptable Diet among 6–23 Months Age Children in Ethiopia: A Multilevel Analysis of The Ethiopian Demographic Health Survey

2018 ◽  
Author(s):  
Aberash abay ◽  
Dejen Yemane ◽  
Abate Bekele ◽  
Beyene Meressa
Keyword(s):  
Logistic Regression ◽  
Health Survey ◽  
Community Context ◽  
Community Level ◽  
P Value ◽  
Multilevel Logistic Regression ◽  
Cross Sectional ◽  
Nutritional Interventions ◽  
Individual Level ◽  
The Individual

AbstractBackgroundThough infant and young children should be fed according to a minimum acceptable diet to ensure appropriate growth and development, only 7% of Ethiopian 6-23 months age children meet the minimum acceptable dietary standards, which is lower than the national target of 11% set for 2016. Therefore, this study aims to assess the individual and community level determinants of minimum acceptable diet among 6–23 months age children in Ethiopia.MethodsThis study analyzed retrospectively a cross-sectional data on a weighted sample of 2919 children aged 6-23 months nested within 617 clusters after extracting from Ethiopian Demographic and Health Survey 2016 via the link www.measuredhs.com. By employing bi-variate multilevel logistic regression model, variables which were significant at the p-value < 25 were included in multivariable multilevel logistic regression analysis. Finally, variables with p-value < 0.05 were considered as significant predictors of minimum acceptable diet.ResultsOnly 6.1% of 6-23 months age children feed minimum acceptable diet in Ethiopia. Children 18-23 months age (AOR=3.7, 95%CI 1.9, 7.2), father’s with secondary or higher education (AOR=2.1, 95%CI 1.2, 3.6), Employed mothers (AOR=1.7, 95%CI 1.2, 2.5), mothers have access to drinking water (AOR=1.9, 95%CI 1.2, 2.9), mothers with media exposure (AOR=2.1 95%CI 1.1, 2.7) were positive individual level predictors. Urban mothers (AOR=4.8, 95%CI 1.7, 13.2)) and agrarian dominant region (AOR=5.6, 95%CI 2.2, 14.5) were community level factors that significantly associated with minimum acceptable diet of 6–23 months age children.ConclusionBoth individual and community level factors were significantly associated with minimum acceptable diet of 6-23 months age children in Ethiopia, suggesting that nutritional interventions designed to improve child health should not only be implemented at the individual level but tailored to community context as well.

scholarly journals Can education be personalised using pupils’ genetic data?

2019 ◽  
Author(s):  
Tim T Morris ◽  
Neil M Davies ◽  
George Davey Smith
Keyword(s):  
Predictive Power ◽  
Predictive Accuracy ◽  
Educational Performance ◽  
Phenotypic Data ◽  
Individual Level ◽  
Polygenic Scores ◽  
Prior Achievement ◽  
Using Data ◽  
The Individual ◽  
Potential Tool

AbstractThe increasing predictive power of polygenic scores for education has led to their promotion by some as a potential tool for genetically informed policy. How well polygenic scores predict educational performance conditional on other phenotypic data is however not well understood. Using data from a UK cohort study, we investigated how well polygenic scores for education predicted pupils’ realised achievement over and above phenotypic data that are available to schools. Across our sample, prediction of educational outcomes from polygenic scores were inferior to those from parental socioeconomic factors. There was high overlap between the polygenic score and achievement distributions, leading to weak predictive accuracy at the individual level. Furthermore, conditional on prior achievement polygenic scores were not predictive of later achievement. Our results suggest that while polygenic scores can be informative for identifying group level differences, they currently have limited use for predicting individual educational performance or for personalised education.

Digital Divide and Broadband Access in an Italian Region

2011 ◽  
pp. 160-176 ◽  
Author(s):  
Enrico Ferro ◽  
J. Ramon Gil-Garcia ◽  
Natalie Helbig
Keyword(s):  
Digital Divide ◽  
Broadband Access ◽  
Skills Acquisition ◽  
Italian Region ◽  
Individual Level ◽  
Starting Point ◽  
Policies And Programs ◽  
The Individual ◽  
The Relationship ◽  
It Skills

Reducing the digital divide in order to build an information society for all is one of the top priorities for European policymakers. A better understanding of the determinants of broadband access at the individual level represents a key starting point for any e-inclusion policy. Based on a review of the literature on digital divide and broadband access, we document different approaches to understanding the digital divide and argue that these perspectives can also help to understand broadband access. Combining the digital divide and broadband literature provides a systematic and theory-based approach to the selection and inclusion of variables in different models. This chapter presents the results of a survey conducted in an Italian region. We provide some implications of our findings and argue that policymakers should explore the relationship between IT skills acquisition, broadband access, and Internet use in order to develop more effective policies and programs.

A Theoretical Framework for IT Consumerization

2019 ◽  
pp. 114-129 ◽  
Author(s):  
Ibrahim Arpaci
Keyword(s):  
Technology Acceptance ◽  
Theoretical Framework ◽  
Bring Your Own Device ◽  
Organizational Level ◽  
Structured Interviews ◽  
Privacy And Security ◽  
Individual Level ◽  
Innovation Diffusion Theory ◽  
Ict Adoption ◽  
The Individual

The chapter provided a comprehensive review of previous studies on the adoption of information and communication technology (ICT). The study further conducted a qualitative study on the adoption of “bring your own device” (BYOD). The study systematically reviewed technology acceptance theories and models such as TAM, TPB, and UTAUT at the individual level and technology adoption theories such as “innovation diffusion theory,” “technology-organization-environment framework,” and “institutional theory” at the organizational level. Thereby, key factors predicting the ICT adoption at the individual, organizational, institutional, and environmental level were identified. A theoretical framework that explains the ICT adoption and the consumerization process was proposed based on the theories. The qualitative data collected by semi-structured interviews with senior-level managers was analyzed using the content analysis. The findings suggested that perceived financial cost, compatibility, privacy, and security concerns were significant factors in predicting the enterprise's adoption of BYOD.

A Spatial Analysis of Male and Female Unemployment in the USA

2015 ◽  
pp. 1797-1809
Author(s):  
Edmund J. Zolnik
Keyword(s):  
Multilevel Models ◽  
Personal Characteristics ◽  
Policy Implications ◽  
Men And Women ◽  
Male And Female ◽  
Individual Level ◽  
Right To Work ◽  
The Usa ◽  
The Individual ◽  
The U.S

An analysis of male and female unemployment in the U.S. explores how gender affects spatial variation in unemployment. The effects of spatially-unlagged and spatially-lagged unemployment rates on the likelihood that individual men and women are unemployed are also explored. Using a recent tabulation of microdata from the American Community Survey, multilevel models of male and female unemployment are fit. Results indicate that age and occupation at the individual-level and a right-to-work dummy at the PUMA-level are the variables that best distinguish unemployed men and women. Results also indicate that unemployment for men is more clustered in space than unemployment for women. Finally, results indicate that the vast majority of the variation in unemployment for individuals in the U.S. is attributable to the personal characteristics of unemployed men and women, not the locational characteristics of high-unemployment places. The paper concludes with a discussion of the policy implications of the latter result.

Social Interactions and the Digital Divide: Identification and Policy Implications

2006 ◽  
Vol 5 (1) ◽  
Author(s):  
Raffaele Miniaci ◽  
Maria Laura Parisi
Keyword(s):  
Social Interactions ◽  
Digital Divide ◽  
Peer Effects ◽  
Computer Literacy ◽  
Computer Skills ◽  
Continuous Variable ◽  
Policy Implications ◽  
Individual Probability ◽  
The Individual

AbstractIn the light of recent policies aiming at raising the computer literacy of young generations and at reducing the digital divide, this paper analyzes to what extent the probability of an individual having computer abilities is affected by the computer skills of her household's other members, i.e. if there are significant within household peer effects. We show how peer effects can be identified when skills are measured with a continuous variable and the learning costs are increasing and convex. Our application on a sample of Italian households indicates that peer abilities within a family significantly increase the individual probability of being skilled.

scholarly journals Individual response to exercise training - a statistical perspective

2015 ◽  
Vol 118 (12) ◽  
pp. 1450-1459 ◽  
Author(s):  
Anne Hecksteden ◽  
Jochen Kraushaar ◽  
Friederike Scharhag-Rosenberger ◽  
Daniel Theisen ◽  
Stephen Senn ◽  
...  
Keyword(s):  
Exercise Training ◽  
Predictive Accuracy ◽  
Signal To Noise Ratio ◽  
Interactive Effects ◽  
Control Group ◽  
Individual Response ◽  
Individual Level ◽  
Exercise Training Program ◽  
The Individual ◽  
Response To Exercise

In the era of personalized medicine, interindividual differences in the magnitude of response to an exercise training program (subject-by-training interaction; “individual response”) have received increasing scientific interest. However, standard approaches for quantification and prediction remain to be established, probably due to the specific considerations associated with interactive effects, in particular on the individual level, compared with the prevailing investigation of main effects. Regarding the quantification of subject-by-training interaction in terms of variance components, confounding sources of variability have to be considered. Clearly, measurement error limits the accuracy of response estimates and thereby contributes to variation. This problem is of particular importance for analyses on the individual level, because a low signal-to-noise ratio may not be compensated by increasing sample size (1 case). Moreover, within-subject variation in training efficacy may contribute to gross response variability. This largely unstudied source of variation may not be disclosed by comparison to a control group but calls for repeated interventions. A second critical point concerns the prediction of response. There is little doubt that exercise training response is influenced by a multitude of determinants. Moreover, indications of interaction between influencing factors of training efficacy lead to the hypothesis that optimal predictive accuracy may be attained using an interactive rather than additive approach. Taken together, aiming at conclusive inference and optimal predictive accuracy in the investigation of subject-by-training interaction entails specific requirements that are deducibly based on statistical principles but beset with many practical difficulties. Therefore, pragmatic alternatives are warranted.

Sign in / Sign up

Export Citation Format

Share Document