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In 2015, the United Nations approved the 2030 Agenda defining 17 Sustainable Development Goals (SDGs), and 169 targets. Among those, the target 12.6 encourages companies to adopt sustainable practices and to integrate sustainability information into their reporting cycle. Thus, the aim of this paper is to understand whether ISO certification is a determinant factor in SDGs reporting. Standalone non-financial reports of the largest Portuguese companies were collected from 2016 until 2020, obtaining a total of 119 reports from 41 companies: 27 (22.7%) of the reports corresponds to non-certified companies and 92 (77.3%) to certified ones. Through a content analysis of the non-financial reports, an SDG disclosure Index (SDG_IND) was developed, to measure the level of disclosure on SDG. A set of panel data based on a Tobit regression analysis was applied, in STATA software, using the total of observations during the period 2016–2020, to verify if the variable ISO certification explains the level of SDGs disclosure. Contrary to our expectation, we did not find significant differences between certified and non-certified companies concerning the SDG-related disclosure. As far as we are aware, previous research in SDG has not considered the linkage with ISO certification. This article aims to explore this gap by investigating differences between certified and non-certified companies, regarding SDG disclosure, as whether ISO certification is a determinant factor of such disclosure.

By applying targeted graph algorithms, the method used by the authors enables effective prediction of user interactions and thus fulfils the complex requirements of modern recommender systems. This study sets a new benchmark for multidimensional recommendation strategies and offers a path towards more advanced and user-centric models.

To improve multidimensional data recommendation systems, multiplex graph structures are useful to capture various types of user interactions. This paper presents a novel framework that uses a graph database to compute and manipulate multiplex graphs. The approach enables flexible dimension management and increases expressive power through a specialised algebra designed for multiplex graph manipulation.

The authors compare the multiplex graph approach with traditional matrix methods, in particular random walk with restart, and show that the method not only provides deeper insights into user preferences by integrating scores from different layers of the multiplex graph, but also outperforming matrix-based approaches in most configurations. The results highlight the potential of multiplex graphs for developing sophisticated and customised recommender systems that significantly improve both performance and explainability.

The study provides a formal specification of a multiplex graph construction based on interaction and content-based information; and the study also developed an algebra dedicated to multiplex graphs, enabling robust and precise graph manipulations necessary for effective recommendation queries. The authors implement these algebraic operations within the Neo4j graph database system with a thorough analysis and experimentation with three different data sets, benchmarked against traditional matrix-based methods.

This study aims to learn about the experiences of inmates who experienced long periods of isolation due to a COVID-19 outbreak in the Brians 1 penitentiary centre. This approach is relevant, as it sought to understand the experiences from the perspective of the prisoners during periods of isolation. The aim was to gain in-depth knowledge, based on the idiosyncrasies of this population, of their emotions and coping strategies in the prison context. This information that may be useful to prison institutions and prison primary healthcare teams to guide the organisation in future health emergencies involving the isolation of prisoners.

A qualitative interpretative phenomenological study was conducted. Face-to-face semi-structured interviews were conducted with a sample of 30 people who had undergone a period of isolation due to a COVID-19 outbreak in one or two of the last two outbreaks at the Brians 1 (Barcelona) prison in 2022, in the days following periods of social isolation. The interviews were transcribed and analysed using the content analysis approach, and were coded using the NVivo 12 qualitative software. The credibility and validity of the data analysed were increased through triangulation at different levels. In this study, data was collected from a heterogeneous sample of prisoners, capturing different views among the prison population.

This research gave us the opportunity to collect prisoners’ accounts of isolation due to COVID-19, in which it became clear that it conditioned the management of time and space in daily prison life. The restrictions amplified negative emotions such as anxiety, stress and restlessness and led to disruptions in communication with the outside world, daily prison activities and judicial processes. Despite these changes, the prisoners understood the imperatives of isolation and the need to adapt to the new situation for a limited period of time. Faced with the detrimental effect on their well-being, the prisoners employed coping strategies focused on emotional management, social supports and occupational engagement.

This study is subject to several limitations related to the characteristics of the sample. No women participated in the study as the modules studied were exclusively for men. People with impaired cognitive abilities, were not included. With regard to the method, it is understood that conducting the interviews in the days after the isolation may have influenced the content and enthusiasm of the participants. Despite these limitations, we are confident that the data triangulation may have given us reliable insight that will further our knowledge of prisoners’ experiences in this type of situation.

The issue of the negative impact of restrictive measures in the prison environment has rarely been studied from the perspective of prisoners. To the best of the authors’ knowledge, this study is the first to provide qualitative data on the experiences of prisoners during periods of social isolation due to COVID-19 outbreaks in prisons in Catalonia (Spain). The narratives allowed the authors to determine what impact the restrictions had on the emotional well-being and daily life of the prison population, information that can help prison institutions and healthcare teams understand how prisoners experienced this type of situation. The authors were also able to carry out an in-depth study of the coping strategies used by the prisoners to deal with negative emotions during the COVID-19 outbreaks, which may serve to guide the organisation of material and human resources in future emergencies or regimented situations involving social isolation.