scholarly journals Predicting Violence in Merseyside: a Network-Based Approach Using No Demographic Information

2020 ◽  
Vol 4 (3-4) ◽  
pp. 89-102
Author(s):  
Paolo Campana ◽  
Andrea Giovannetti
Keyword(s):  
Regression Models ◽  
Predictive Power ◽  
Demographic Information ◽  
Data Set ◽  
Logistic Regression Models ◽  
Individual Level ◽  
The Individual ◽  
High Level ◽  
Very High ◽  
Individual Information

Abstract Purpose We explore how we can best predict violent attacks with injury using a limited set of information on (a) previous violence, (b) previous knife and weapon carrying, and (c) violence-related behaviour of known associates, without analysing any demographic characteristics. Data Our initial data set consists of 63,022 individuals involved in 375,599 events that police recorded in Merseyside (UK) from 1 January 2015 to 18 October 2018. Methods We split our data into two periods: T1 (initial 2 years) and T2 (the remaining period). We predict “violence with injury” at time T2 as defined by Merseyside Police using the following individual-level predictors at time T1: violence with injury; involvement in a knife incident and involvement in a weapon incident. Furthermore, we relied on social network analysis to reconstruct the network of associates at time T1 (co-offending network) for those individuals who have committed violence at T2, and built three additional network-based predictors (associates’ violence; associates’ knife incident; associates’ weapon incident). Finally, we tackled the issue of predicting violence (a) through a series of robust logistic regression models using a bootstrapping method and (b) through a specificity/sensitivity analysis. Findings We found that 7720 individuals committed violence with injury at T2. Of those, 2004 were also present at T1 (27.7%) and co-offended with a total of 7202 individuals. Regression models suggest that previous violence at time T1 is the strongest predictor of future violence (with an increase in odds never smaller than 123%), knife incidents and weapon incidents at the individual level have some predictive power (but only when no information on previous violence is considered), and the behaviour of one’s associates matters. Prior association with a violent individual and prior association with a knife-flagged individual were the two strongest network predictors, with a slightly stronger effect for knife flags. The best performing regressors are (a) individual past violence (36% of future violence cases correctly identified); (b) associates’ past violence (25%); and (c) associates’ knife involvement (14%). All regressors are characterised by a very high level of specificity in predicting who will not commit violence (80% or more). Conclusions Network-based indicators add to the explanation of future violence, especially prior association with a knife-flagged individual and association with a violent individual. Information about the knife involvement of associates appears to be more informative than a subject’s own prior knife involvement.

scholarly journals Differences in Sickness Allowance Receipt between Swedish Speakers and Finnish Speakers in Finland

2017 ◽  
Vol 52 ◽  
pp. 43-58 ◽  
Author(s):  
Kaarina S. Reini ◽  
Jan Saarela
Keyword(s):  
Regression Models ◽  
Health Condition ◽  
Logistic Regression Models ◽  
Individual Level ◽  
Objective Health ◽  
Language Groups ◽  
Health Measure ◽  
All Cause Mortality ◽  
The Difference ◽  
The Individual

Previous research has documented lower disability retirement and mortality rates of Swedish speakers as compared with Finnish speakers in Finland. This paper is the first to compare the two language groups with regard to the receipt of sickness allowance, which is an objective health measure that reflects a less severe poor health condition. Register-based data covering the years 1988-2011 are used. We estimate logistic regression models with generalized estimating equations to account for repeated observations at the individual level. We find that Swedish-speaking men have approximately 30 percent lower odds of receiving sickness allowance than Finnish-speaking men, whereas the difference in women is about 15 percent. In correspondence with previous research on all-cause mortality at working ages, we find no language-group difference in sickness allowance receipt in the socially most successful subgroup of the population.

scholarly journals The Impact of Customer Contact on Collective Human Energy in Firms

2018 ◽  
Vol 44 (5) ◽  
pp. 915-952
Author(s):  
Petra Kipfelsberger ◽  
Heike Bruch ◽  
Dennis Herhausen
Keyword(s):  
Transformational Leadership ◽  
Organizational Level ◽  
Data Set ◽  
Customer Contact ◽  
Individual Level ◽  
Moderated Mediation Model ◽  
Human Energy ◽  
The Individual ◽  
High Level ◽  
The Impact

This article investigates how and when a firm’s level of customer contact influences the collective organizational energy. For this purpose, we bridge the literature on collective human energy at work with the job impact framework and organizational sensemaking processes and argue that a firm’s level of customer contact is positively linked to the collective organizational energy because a high level of customer contact might make the experience of prosocial impact across the firm more likely. However, as prior research at the individual level has indicated that customers could also deplete employees’ energy, we introduce transformational leadership climate as a novel contingency factor for this linkage at the organizational level. We propose that a medium to high transformational leadership climate is necessary to derive positive meaning from customer contact, whereas firms with a low transformational leadership climate do not get energized by customer contact. We tested the proposed moderated mediation model with multilevel modeling and a multisource data set comprising 9,094 employees and 75 key informants in 75 firms. The results support our hypotheses and offer important theoretical contributions for research on collective human energy in organizations and its interplay with customers.

Preference Voting in Italy

1985 ◽  
Vol 18 (2) ◽  
pp. 229-249 ◽  
Author(s):  
RICHARD S. KATZ
Keyword(s):  
Political Culture ◽  
Regression Models ◽  
Contextual Effects ◽  
Full Account ◽  
Logistic Regression Models ◽  
Individual Level ◽  
Representation Systems ◽  
Preference Voting ◽  
Important Possibility ◽  
The Individual

Intraparty preference voting is a potentially important possibility for voters in many proportional representation systems, especially the Italian system. Three hypotheses—that preference voting is an indicator of traditionalism or the voto di scambio, sophistication or the voto d'opinione, and mobilization or the voto d'appartenenza—are considered using survey data and logistic regression models. All three hypotheses are supported by the data. Although the support for the individual-level traditionalism account is weakest, the data suggest that traditional political culture may contribute to the contextual prerequisites for sophistication or mobilization to lead to preference voting. Overall, it is suggested that the three explanations are complementary rather than contradictory, and that contextual effects must be considered in a full account of preference voting.

Fair-Wages for People With Disabilities: Barriers and Facilitators

2020 ◽  
Vol 31 (3) ◽  
pp. 152-163
Author(s):  
Carli Friedman ◽  
Mary C. Rizzolo
Keyword(s):  
Regression Models ◽  
People With Disabilities ◽  
Binary Logistic Regression ◽  
Service Organizations ◽  
Organizational Level ◽  
Logistic Regression Models ◽  
Individual Level ◽  
Problematic Issue ◽  
Fair Wages ◽  
The Individual

Subminimum wage is a prominent and problematic issue affecting the lives of many people with disabilities. For this reason, the aim of this study was to identify the correlates of fair-wages (at least minimum wage) for people with disabilities—which factors facilitate and hinder people with disabilities’ access to fair-wages. We utilized Personal Outcome Measures® interview data from approximately 1,500 people with disabilities to examine how individual, employment, and organizational-level factors correlate with people with disabilities’ access to fair-wages. Binary logistic regression models revealed at the individual-level support needs, guardianship, and residence type all significantly correlate with people with disabilities’ odds of receiving fair-wages. In addition, the ability to experience a number of employment options, as well as decide where to work, produce higher odds of having fair-wages. Finally, our findings also revealed the key role service organizations can play in facilitating people with disabilities’ access to fair-wages. Attention to the facilitators that promote access to fair-wages for people with disabilities, and the barriers that hinder this access is one of the first steps toward ending this discrimination against people with disabilities.

Territorial Distribution of Alcohol and Drug Addictions Mortality Concerning Regional Disparities in the Slovak Republic from Year 1996 to Year 2015

2020 ◽  
Keyword(s):  
Mortality Rate ◽  
Slovak Republic ◽  
Regional Disparities ◽  
Point Of View ◽  
Extreme Position ◽  
Data Set ◽  
Female Sex ◽  
Male Sex ◽  
The Individual ◽  
High Level

BACKGROUND: This paper deals with territorial distribution of the alcohol and drug addictions mortality at a level of the districts of the Slovak Republic. AIM: The aim of the paper is to explore the relations within the administrative territorial division of the Slovak Republic, that is, between the individual districts and hence, to reveal possibly hidden relation in alcohol and drug mortality. METHODS: The analysis is divided and executed into the two fragments – one belongs to the female sex, the other one belongs to the male sex. The standardised mortality rate is computed according to a sequence of the mathematical relations. The Euclidean distance is employed to compute the similarity within each pair of a whole data set. The cluster analysis examines is performed. The clusters are created by means of the mutual distances of the districts. The data is collected from the database of the Statistical Office of the Slovak Republic for all the districts of the Slovak Republic. The covered time span begins in the year 1996 and ends in the year 2015. RESULTS: The most substantial point is that the Slovak Republic possesses the regional disparities in a field of mortality expressed by the standardised mortality rate computed particularly for the diagnoses assigned to the alcohol and drug addictions at a considerably high level. However, the female sex and the male sex have the different outcome. The Bratislava III District keeps absolutely the most extreme position. It forms an own cluster for the both sexes too. The Topoľčany District bears a similar extreme position from a point of view of the male sex. All the Bratislava districts keep their mutual notable dissimilarity. Contrariwise, evaluation of a development of the regional disparities among the districts looks like notably heterogeneously. CONCLUSIONS: There are considerable regional discrepancies throughout the districts of the Slovak Republic. Hence, it is necessary to create a common platform how to proceed with the solution of this issue.

Challenging the Link Between Early Childhood Television Exposure and Later Attention Problems: A Multiverse Approach

2021 ◽  
pp. 095679762097165
Author(s):  
Matthew T. McBee ◽  
Rebecca J. Brand ◽  
Wallace E. Dixon
Keyword(s):  
Early Childhood ◽  
Regression Models ◽  
Propensity Score Analysis ◽  
Harmful Effect ◽  
Attention Problems ◽  
Linear Regression Models ◽  
Data Set ◽  
Logistic Regression Models ◽  
Score Analysis ◽  
Television Exposure

In 2004, Christakis and colleagues published an article in which they claimed that early childhood television exposure causes later attention problems, a claim that continues to be frequently promoted by the popular media. Using the same National Longitudinal Survey of Youth 1979 data set ( N = 2,108), we conducted two multiverse analyses to examine whether the finding reported by Christakis and colleagues was robust to different analytic choices. We evaluated 848 models, including logistic regression models, linear regression models, and two forms of propensity-score analysis. If the claim were true, we would expect most of the justifiable analyses to produce significant results in the predicted direction. However, only 166 models (19.6%) yielded a statistically significant relationship, and most of these employed questionable analytic choices. We concluded that these data do not provide compelling evidence of a harmful effect of TV exposure on attention.

Association Between Opioid Use and Diabetes in Patients With Ankle Fracture Repair

2021 ◽  
pp. 107110072110581
Author(s):  
Wenye Song ◽  
Naohiro Shibuya ◽  
Daniel C. Jupiter
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Ankle Fracture ◽  
Regression Models ◽  
Fracture Repair ◽  
Opioid Use ◽  
Data Set ◽  
Opioid Prescription ◽  
Logistic Regression Models ◽  
Patients With Diabetes

Background: Ankle fractures in patients with diabetes mellitus have long been recognized as a challenge to practicing clinicians. Ankle fracture patients with diabetes may experience prolonged healing, higher risk of hardware failure, an increased risk of wound dehiscence and infection, and higher pain scores pre- and postoperatively, compared to patients without diabetes. However, the duration of opioid use among this patient cohort has not been previously evaluated. The purpose of this study is to retrospectively compare the time span of opioid utilization between ankle fracture patients with and without diabetes mellitus. Methods: We conducted a retrospective cohort study using our institution’s TriNetX database. A total of 640 ankle fracture patients were included in the analysis, of whom 73 had diabetes. All dates of opioid use for each patient were extracted from the data set, including the first and last date of opioid prescription. Descriptive analysis and logistic regression models were employed to explore the differences in opioid use between patients with and without diabetes after ankle fracture repair. A 2-tailed P value of .05 was set as the threshold for statistical significance. Results: Logistic regression models revealed that patients with diabetes are less likely to stop using opioids within 90 days, or within 180 days, after repair compared to patients without diabetes. Female sex, neuropathy, and prefracture opioid use are also associated with prolonged opioid use after ankle fracture repair. Conclusion: In our study cohort, ankle fracture patients with diabetes were more likely to require prolonged opioid use after fracture repair. Level of Evidence: Level III, prognostic.

A Critical Review of Theories and Models of Technology Adoption and Acceptance in Information System Research

2015 ◽  
Vol 6 (4) ◽  
pp. 58-77 ◽  
Author(s):  
Ali Tarhini ◽  
Nalin Asanka Gamagedara Arachchilage ◽  
Ra'ed Masa'deh ◽  
Muhammad Sharif Abbasi
Keyword(s):  
Information System ◽  
Technology Adoption ◽  
Environmental Factors ◽  
Critical Review ◽  
Predictive Power ◽  
Theoretical Models ◽  
System Research ◽  
Information System Research ◽  
Individual Level ◽  
The Individual

Previous research shows that selecting an appropriate theory or model has always remained a critical task for IS researchers. To the best of the authors' knowledge, there are few papers that review and compare the acceptance theories and models at the individual level. Hence, this article aims to overcome this problem by providing a critical review of eight of the most influential theories that have been used to predict and explain human behaviour towards adoption of various technologies at the individual level. This article also summarizes their evolution; highlight the key constructs, extensions, strengths, and criticisms from a selective list of published articles appeared in the literature related to IS. This review provides a holistic picture for future researchers in selecting appropriate single/multiple theoretical models/constructs based on their strengths and weaknesses and in terms of predictive power and path significance. It is concluded that a well-established theory should consider the personal, social, cultural, technological, organizational and environmental factors

Cardiovascular risk estimation at the individual level

ESC CardioMed ◽  
2018 ◽  
pp. 846-863
Author(s):  
Yvo M. Smulders ◽  
Marie-Therese Cooney ◽  
Ian Graham
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Risk ◽  
High Risk ◽  
Risk Estimation ◽  
Pharmacological Therapy ◽  
Cardiovascular Risks ◽  
Individual Level ◽  
The Individual ◽  
Very High ◽  
Cardiovascular Risk Estimation

The absolute benefit of any measure to prevent cardiovascular disease, be it lifestyle improvement or pharmacological therapy, depends on the baseline cardiovascular risk. This risk cannot be assessed exactly, but only be estimated because many known risk determinants cannot be accounted for in existing risk scoring systems, and because the application to an individual of risk estimates derived from populations is imprecise. Several cardiovascular risk estimation methods are available, and the European Society of Cardiology has favoured the European-based Systematic COronary Risk Evaluation (SCORE) system as a basis for their cardiovascular disease prevention guidelines. SCORE estimates absolute 10-year cardiovascular mortality risk. In specific circumstances, estimation of relative risk, risk age, or lifetime risk may be considered. High- and very-high-risk population are defined by SCORE risks greater than 5% and greater than 10%, respectively, or by clinical conditions conferring (very) high risk, such as existing cardiovascular disease or chronic kidney disease. The role of additional risk information on top of the information entered in SCORE is generally limited. In particular, markers of early cardiovascular damage should be collected and interpreted with caution. Absolute cardiovascular risks in young and elderly individuals are almost always low or very high, respectively, and the options for appropriate interpretation and management of these risks are discussed.

Levels of Aggregation in Conjoint Analysis: An Empirical Comparison

1980 ◽  
Vol 17 (4) ◽  
pp. 516-523 ◽  
Author(s):  
William L. Moore
Keyword(s):  
Conjoint Analysis ◽  
Predictive Power ◽  
Aggregate Level ◽  
Segmentation Method ◽  
Empirical Comparison ◽  
Individual Level ◽  
Aggregate Analysis ◽  
The Individual ◽  
Level Analysis

Two segmented methods of performing conjoint anal/sis, clustered and componential segmentation, are compared with each other as well as with individual level and totally aggregate level analyses. The two segmented methods provide insights to the data that (1) are not obtainable at the aggregate level and (2) are in a form that is more easily communicated than the information from the individual level analysis. The predictive power of the clustered segmentation method is higher than that of componential segmentation, and both are superior to the aggregate analysis but inferior to individual level analysis.

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