Young people,social workers and social work education: the role of digital skills

ABSTRACT

This paper addresses a key issue in the development of youth-focused social work: the role of digital skills in the relationship between young people and social workers who work with these native digital users. To this end, we analysed data from the International Digital Economy and Society Index 2019 and Eurostat. Information from the sixth European Working Conditions Survey and a survey conducted by the Social Care Institute for Excellence and the British Association of Social Workers supported the empirical analysis. The main findings reveal a gap between the level of digital skills required in the labour market and the actual level of digital skills in both young people and social workers, despite efforts by both groups to improve their skills. Initiatives to foster digital skills are therefore recommended to bridge this digital divide. Lastly, it was concluded that both groups could act as mutual drivers of digital transformation.     

A new value stream mapping approach for healthcare environments

Hospitals worldwide are giving a growing emphasis to the application of lean concepts in the healthcare sector, commonly known as ‘lean healthcare’. A fundamental tool that allows such implementations is the value stream mapping (VSM). The problem is that VSM models used in implementations of lean healthcare are simple adaptations of the original VSM model, which was initially directed towards manufacturing and may not always represent important support activities for the patient flow that directly impact treatment time. Within this context, this paper presents a new VSM approach for healthcare environments. This new VSM model, specifically designed for healthcare environments, contemplates all activities that directly affect the treatment time. In addition, the present paper also presents an action research in a Brazilian hospital where the proposed VSM model is compared to other VSM models found in the literature. The results shown that the proposed VSM model was able to identify some operational bottlenecks and wastes that interfere in the patient’s treatment that could not be identified by other mapping models studied.     

A Structural Model of Government Formation

In this paper we estimate a bargaining model of government formation in parliamentary democracies. We use the estimated structural model to conduct constitutional experiments aimed at evaluating the impact of institutional features of the political environment on the duration of the government formation process, the type of coalitions that form, and their relative stability.     

Demographics,Public Spending and Social Programs

The demographic trends of the population of Italy are characterized by a very low fertility rate (in the 1990s the total fertility rate was 1.1–1.3, i.e. one of the lowest in the world) and very rapid aging (Italy was the first country in the world in which people aged 60+ outnumbered people aged less than 20). These trends require continuous and deep changes in the organization of society and in public services to avoid an increasing imbalance between demand and supply. They also require new social policies based on equity, efficiency and rationality.     

Embedding latent class regression and latent class distal outcome models into cluster-weighted latent class analysis: a detailed simulation experiment

Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class-specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster-weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands.     

On some mixture models based on the Birnbaum-Saunders distribution and associated inference

In this paper, we consider three different mixture models based on the Birnbaum-Saunders (BS) distribution, viz., (1) mixture of two different BS distributions, (2) mixture of a BS distribution and a length-biased version of another BS distribution, and (3) mixture of a BS distribution and its length-biased version. For all these models, we study their characteristics including the shape of their density and hazard rate functions. For the maximum likelihood estimation of the model parameters, we use the EM algorithm. For the purpose of illustration, we analyze two data sets related to enzyme and depressive condition problems. In the case of the enzyme data, it is shown that Model 1 provides the best fit, while for the depressive condition data, it is shown all three models fit well with Model 3 providing the best fit.     

Toward Defining the Causal Role of Consciousness: Using Models of Memory and Moral Judgment from Cognitive Neuroscience to Expand the Sociological Dual‐Process Model

What role does “discursive consciousness” play in decision‐making? How does it interact with “practical consciousness?” These two questions constitute two important gaps in strong practice theory that extend from Pierre Bourdieu's habitus to Stephen Vaisey's sociological dual‐process model and beyond. The goal of this paper is to provide an empirical framework that expands the sociological dual‐process model in order to fill these gaps using models from cognitive neuroscience. In particular, I use models of memory and moral judgment that highlight the importance of executive functions and semantic memory. I outline each model as it pertains to the aforementioned gaps in strong practice theory. I then use the models from cognitive neuroscience to create an expanded dual‐process model that addresses how and when conscious mental systems override and interact with subconscious mental systems in the use of cultural ends for decision‐making. Finally, using this expanded model I address the sociological debate over the use of interview and survey data. My analysis reveals that surveys and interviews both elicit information encoded in declarative memory and differ primarily in the process of information retrieval that is required of respondents.     

Two-tailed asymptotic inferences for a proportion

This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n≥50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys’ Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.     

Performance of coefficient of variation estimators in ranked set sampling

In this paper, we propose and evaluate the performance of different parametric and nonparametric estimators for the population coefficient of variation considering Ranked Set Sampling (RSS) under normal distribution. The performance of the proposed estimators was assessed based on the bias and relative efficiency provided by a Monte Carlo simulation study. An application in anthropometric measurements data from a human population is also presented. The results showed that the proposed estimators via RSS present an expressively lower mean squared error when compared to the usual estimator, obtained via Simple Random Sampling. Also, it was verified the superiority of the maximum likelihood estimator, given the necessary assumptions of normality and perfect ranking are met.