Iscte – University Institute of Lisbon

Existing evidence indicates sex-related differences in Prescription Opioid Use Disorder (OUD) in Chronic Non-Cancer Pain (CNCP). However to date, there is scant evidence for other socioeconomic factors in these differences. Our aim was to enquire about the influence of gender and drug copayment of OUD narratives by the text mining analysis. A prospective mixed-methods study was designed and performed at Pain Unit (PU) including 238 real world patients with CNCP divided in controls (n = 206) and OUD cases (n = 32) due to DSM-5 diagnosis Variables related to pain, sleep, mental and health status were collected in together with sex and gender interaction, in pain status, along 30-45 min face-to-face interviews. Sex differences were observed due to women’s significantly older ages, with a stronger impact on mental health, and an even stronger one for the OUD women. Globally, OUD cases were more unemployed vs the CNCP controls, and on a significantly higher median opioid daily dose of 90 [100] mg/day. Although OUD participants did more social activities, they tended to use less vocabulary to express themselves regardless of their sex, gender role or economic status. In contrast, the CNCP participants presented more differences driven by their incomes, with “limited” being the most discriminating word for those on low income, followed by “less” and “help”. Here, the most significant word of CNCP women was “husband”, followed by “tasks”. In contrast, gender reproductive roles shared similarities in both sexes, being one of the most discriminatory words “help”. The data show that OUD patients seem to have a marked influence of OUD on poorer lexicon and simpler narrative, together with a significant impact of socioeconomic factors on the CNCP narratives. The conclusion suggests to extend the research to better understand the effect of sex, gender and socioeconomic status in CNCP especially on OUD women’s health.

The growing influence of far-right parties and their connections with security forces poses a significant threat, particularly given the security forces’ monopoly on legitimate violence and the far-right’s inherent distrust of democratic institutions. This article challenges the assumption that the trade union movement uniformly opposes far-right ideologies. Instead, we show that many representative organizations within the security forces actively support far-right initiatives, with police forces especially susceptible to such influence. Drawing on documentary evidence from Brazil and Portugal, our case studies reveal that far-right parties do not necessarily reject intermediary organizations, such as trade unions and professional associations, but rather strategically use them as ‘transmission belts’ to further their agenda. This article contributes to reconsidering the transmission belt concept and suggests pathways for future research in this area.

This paper presents the development of a cohesive set of scientifically grounded recommendations aimed at harmonizing anti-discrimination protections. These recommendations, rooted in multidisciplinary knowledge, address the complexities of sequential, additive, and intersectional multiple discrimination. Through a multidisciplinary approach that combines Law, Social Anthropology, and Economics, this work uses qualitative data to formulate empirically grounded proposals. One of the key recommendations is the adoption of a single law and the establishment of a single entity—the Equality Agency—to eliminate the fragmentation and other institutional challenges identified during fieldwork. By integrating social and legal analysis, the paper proposes a redesign of legal and institutional frameworks to better protect against various forms of discrimination. It acknowledges the structural nature of discrimination and recognizes the need for an integrated response to the complexities of the experiences of those affected. While Portugal serves as the primary context for this research, we believe that the principles, methodologies, and overarching logic of this approach have broader applicability, offering valuable insights for addressing multiple and intersectional discrimination in other contexts.

This study examines the transformation of disused industrial heritage in the eastern area of Lisbon, specifically within the districts of Marvila and Beato, focusing on the dynamics of urban regeneration following deindustrialisation. The research highlights how, in a context characterised—similarly to other Southern European countries—by late-stage deindustrialisation, the industrial legacy of these areas has predominantly been repurposed to accommodate activities associated with the creative and cultural sectors. Using a tripartite methodology comprising a literature review, Geographic Information System (GIS) mapping, and industrial heritage characterisation through direct observation, alongside engagement with the ROCK (Regeneration and Optimisation of Cultural Heritage in Creative and Knowledge Cities) project, the study identified and characterised twelve former factories. Of these, nine have primarily been converted for artistic and cultural use, while two remain abandoned, emphasising the lack of significant public intervention. The article addresses the risks of gentrification and the increasing privatisation of industrial sites, raising concerns about preserving the identity and collective memory of these spaces. It underscores the need for integrated policies to ensure the protection and sustainable management of these sites. The article concludes with reflections on future prospects for safeguarding industrial heritage in urban contexts.

Music training is widely claimed to enhance nonmusical abilities, yet causal evidence remains inconclusive. Moreover, research tends to focus on cognitive over socioemotional outcomes. In two studies, we investigated whether music training improves emotion recognition in voices and faces among school-aged children. We also examined music-training effects on musical abilities, motor skills (fine and gross), broader socioemotional functioning, and cognitive abilities including nonverbal reasoning, executive functions, and auditory memory (short-term and working memory). Study 1 (N = 110) was a 2-year longitudinal intervention conducted in a naturalistic school setting, comparing music training to basketball training (active control) and no training (passive control). Music training improved fine-motor skills and auditory memory relative to controls, but it had no effect on emotion recognition or other cognitive and socioemotional abilities. Both music and basketball training improved gross-motor skills. Study 2 (N = 192) compared children without music training to peers attending a music school. Although music training correlated with better emotion recognition in speech prosody (tone of voice), this association disappeared after controlling for socioeconomic status, musical abilities, or short-term memory. In contrast, musical abilities correlated with emotion recognition in both prosody and faces, independently of training or other confounding variables. These findings suggest that music training enhances fine-motor skills and auditory memory, but it does not causally improve emotion recognition, other cognitive abilities, or socioemotional functioning. Observed advantages in emotion recognition likely stem from preexisting musical abilities and other confounding factors such as socioeconomic status.

Background Artificial intelligence (AI) has shown exponential growth and advancements, revolutionizing various fields, including health care. However, domain adaptation remains a significant challenge, as machine learning (ML) models often need to be applied across different health care settings with varying patient demographics and practices. This issue is critical for ensuring effective and equitable AI deployment. Cardiovascular diseases (CVDs), the leading cause of global mortality with 17.9 million annual deaths, encompass conditions like coronary heart disease and hypertension. The increasing availability of medical data, coupled with AI advancements, offers new opportunities for early detection and intervention in cardiovascular events, leveraging AI’s capacity to analyze complex datasets and uncover critical patterns. Objective This review aims to examine AI methodologies combined with medical data to advance the intelligent monitoring and detection of CVDs, identifying areas for further research to enhance patient outcomes and support early interventions. Methods This review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology to ensure a rigorous and transparent literature review process. This structured approach facilitated a comprehensive overview of the current state of research in this field. Results Through the methodology used, 64 documents were retrieved, of which 40 documents met the inclusion criteria. The reviewed papers demonstrate advancements in AI and ML for CVD detection, classification, prediction, diagnosis, and patient monitoring. Techniques such as ensemble learning, deep neural networks, and feature selection improve prediction accuracy over traditional methods. ML models predict cardiovascular events and risks, with applications in monitoring via wearable technology. The integration of AI in health care supports early detection, personalized treatment, and risk assessment, possibly improving the management of CVDs. Conclusions The study concludes that AI and ML techniques can improve the accuracy of CVD classification, prediction, diagnosis, and monitoring. The integration of multiple data sources and noninvasive methods supports continuous monitoring and early detection. These advancements help enhance CVD management and patient outcomes, indicating the potential for AI to offer more precise and cost-effective solutions in health care.

Despite the substantial proliferation of hybrid work, little has been done to reconcile extant individual‐ and team‐level perspectives. This is problematic because it does not acknowledge how individuals' hybrid work practices constrain team‐level interactions and subsequent outcomes. Specifically, the extant literature does not yet capture the complex configurations that result from team members alternating between co‐located and remote forms of collaboration and how these may provoke the formation of subgroups within the team. In this conceptual paper, we introduce the construct co‐location imbalance , which we define as the disparity in co‐location between different combinations of team members, as a way of capturing geographic configurations in hybrid teams. Through illustrative hybrid teamwork archetypes, we demonstrate the meaning and implications of co‐location imbalance on subgroup formation. We then map out a nomological network surrounding co‐location imbalance and derive testable propositions on its temporal dynamics and antecedents. Our paper concludes with a discussion of our research's theoretical and practical contributions and directions to advance future research on hybrid teamwork.

Many studies have linked musical expertise with nonmusical abilities such as speech perception, memory, or executive functions. Far fewer have examined associations with basic auditory skills. Here, we asked whether psychoacoustic thresholds predict four aspects of musical expertise: music training, melody perception, rhythm perception, and self-reported musical abilities and behaviors (other than training). A total of 138 participants completed nine psychoacoustic tasks, as well as the Musical Ear Test (melody and rhythm subtests) and the Goldsmiths Musical Sophistication Index. We also measured and controlled for demographics, general cognitive abilities, and personality traits. The psychoacoustic tasks assessed discrimination thresholds for pitch and temporal perception (both assessed with three tasks), and for timbre, intensity, and backward masking (each assessed with one task). Both music training and melody perception predicted better performance on the pitch-discrimination tasks. Rhythm perception was associated with better performance on several temporal and nontemporal tasks, although none had unique associations when the others were held constant. Self-reported musical abilities and behaviors were associated with performance on one of the temporal tasks: duration discrimination. The findings indicate that basic auditory skills correlate with individual differences in musical expertise, whether expertise is defined as music training or musical ability.

Funding: This work was supported by Fundação para a Ciência e a Tecnologia. Keywords: internalisation and externalisation | NEET | perceived social support | perception of stress | quality of life | resilience ABSTRACT The acronym NEET refers to youth aged 15-29 who are not engaged in employment, education or training. Although acknowledged as a social, economic and political problem, existing policies struggle to re-engage NEET youth in formal education or work because of the lack of understanding of their psychological characteristics. This mapping review, guided by PRISMA methodology , aimed to map specific NEETs' psychological characteristics. AI research tools, specifically Elicit and Scispace, streamlined the search process, identifying 1071 articles. After a comprehensive screening process, 10 studies met the inclusion criteria, covering 19,418 NEET youth. The included studies predominantly used correlational designs and focused mainly on challenging psychological characteristics, revealing that NEET status is strongly associated with negative mental health outcomes, including increased stress, anxiety and depressive symptoms, as well as behavioural issues, along with a notable gap in research on protective factors. This review highlights that the existing evidence on NEETs psychological features is mainly correlational, does not include relevant and much-needed qualitative approaches, emphasises challenging psychological outcomes (e.g., internalisation) over positive psychological ones (e.g., resilience) and presents some conceptual overlaps between psychological constructs, which hampers the ability to design effective policies and programs.

Past research has linked sociosexuality and flirting skills to different types of singlehood. Individuals with unrestricted sociosexuality are less likely to enter long-term relationships or experience involuntary singlehood, whereas shyness and low self-confidence are common reasons for involuntary singlehood. However, existing studies tend to focus solely on direct associations between sociosexuality, courtship behaviors, and singlehood status, overlooking potential interaction effects among these factors. In this cross-sectional study of 816 Colombian young adults (487 women and 329 men), we examined whether flirting self-efficacy beliefs mediate the relationship between sociosexuality and singlehood status. Multinomial logistic regression models indicated that higher levels of unrestricted sociosexuality and greater perceived flirting self-efficacy were associated with a decreased likelihood of reporting singlehood due to difficulty finding a partner. Moreover, structural equation models demonstrated that flirting self-efficacy mediates the relationship between sociosexuality and singlehood status. These findings underscore the importance of flirting self-efficacy in the mating process and illuminate pathways through which sociosexuality influences singlehood status in the Latin American context.

This is the protocol for a Campbell systematic review. The objective is as follows: to consolidate the available evidence on attitudinal aspects related to the utilisation of digital technologies in health among older adults. More specifically, we will summarise and systematise the existing reviews findings to identify attitudinal factors that interfere with the use of digital technologies in health in advanced age and to determine whether these factors act as facilitators or barriers. We will also compare the influence of attitudinal factors on technology use behaviour, considering the type of technology in question, and the purpose and context of its use. The overview of reviews questions are the following: (1) What are the attitudinal factors related to the use of digital technologies in health by older adults? (2) Which of these factors facilitate the use of digital technologies in health, and which make it difficult? (3) Are the attitudinal factors that facilitate and make difficult the use of digital technologies in health different for different types of technologies? (4) Are the attitudinal factors that facilitate and make difficult the use of digital technologies in health different for different purposes and contexts of use of these technologies?

Research on psychosocial development and its relation with school is key for adolescent students’ well-being. This study aims to complement existing research by understanding how adolescents‘ psychosocial development and student engagement in school differ according to age and gender. Participants were 708 students in early and late adolescence, including girls and boys. The study used a short version of Erikson’s Psychosocial Stages Inventory and the Student Engagement in School Four-Dimensional Scale. Results showed a significant decline from early to late adolescence for psychosocial trust and identity and all dimensions of student engagement in school. They also stressed the differences between girls and boys, which persisted from early to late adolescence. The results underlined that schools’ difficulty in addressing gender stereotypes and student engagement decreased. These findings challenge schools to go beyond academics and offer specific directions for enhancing adolescents’ psychosocial development and engagement in school.

Healthcare providers face critical challenges in managing and exchanging patient health and medical records. Traditional health and medical data management systems, which often include paper-based records and work as closed, isolated silos, have demonstrated limitations in terms of data usability, interoperability, and patient privacy. This translates into limitations not only for providers but also for the patients, healthcare professionals, and other participants of the health-care value chain, hindering potential innovations and efficiency gains. Distributed Ledger Technology (DLT), such as the blockchain, is emerging as a possible solution to challenges in data management and beyond across several operational and administrative processes in healthcare services. This paper begins with an extensive overview of the literature with an emphasis on DLT implementations and applications in the healthcare industry. We examine how DLT has been used in real-world initiatives across the healthcare domain, highlight notable initiatives, and outline potential improvements. This may result from its adoption, namely in areas such as healthcare data sharing and interoperability, verifiability, transparency, or patient privacy and control. Overall, some of DLT’s native capabilities, such as data immutability, sharing and reconciliation across parties with varying levels of trust, and user self-sovereignty may translate into solutions for several caveats of the current healthcare technological infrastructures, and contribute to improving healthcare outcomes by fostering innovations, enabling broader sharing of healthcare data, enhancing transparency over the use of data, equipping patients with greater control over their data, and enabling new or improved services and processes in healthcare.

International Criminal Courts (ICCs) are guarantors that justice can be achieved for the most egregious crimes against humanity and that surviving victims of those crimes can live with the assurance that the perpetrators will be held accountable for their actions. Those crimes are complex, sensitive and could be used as a weapon for an intervenient’ s own purpose and interests. As such, the credibility of these institutions is often attacked, and it is of critical importance that the process in which they pursue their mandate is rigorous and effective. Evidence sits at the core of the judicial process, and the participants rely on it to be authentic, integer and untampered with to ensure the fairness of the proceedings. Without enforcing powers, these ICCs could rely extensively on evidence provided by other parties to build a strong case from inception to the appeals stage. With the increased digitization of evidence, cyberthreats, size and complexity of evidence, traditional methods of managing the chain of custody are becoming vulnerable to the successful act of challenging the admissibility of evidence. Blockchain could be the answer for strengthening the chain of custody in evidence management, as this technology brings essential characteristics such as timestamping, authentication, immutability and trust among independent parties. This research conceives and designs a blockchainbased framework that maintains a tamperproof chain of custody and multilevel trust in evidence management. It ensures the authenticity and indisputability of evidence in judicial proceedings.

Introduction: Recent advancements in diagnostic imaging technologies have significantly improved the field of dental medicine. This review examines these new imaging techniques and their impact on enhancing accuracy, enabling early detection, and facilitating effective treatment planning in dentistry. Methods: A bibliometric and content analysis was conducted on 61 peer-reviewed articles retrieved from the Scopus database, published between 2019 and 2024. The selection criteria focused on studies exploring advances in dental diagnosis through innovative imaging methods and personalized techniques for identifying oral pathologies. The bibliometric approach analyzed publication trends, while content analysis categorized emerging technologies and their clinical applications. Results: Our findings indicate a notable shift towards integrating cutting-edge technologies, including Cone Beam Computed Tomography (CBCT), artificial intelligence (AI), and biosensors. These advancements have significantly improved diagnostic accuracy, particularly in complex cases such as periodontal diseases, dental fractures, and oral infections. Studies demonstrate that molecular diagnostics and AI-driven algorithms enhance the personalization of treatment plans, optimizing patient outcomes. Conclusions: Emerging diagnostic technologies have the potential to enhance both the quality and efficiency of dental care. However, their implementation is challenged by high costs, the need for specialized training, and disparities in access. Future research should focus on refining AI-driven diagnostic models, addressing regulatory considerations, and expanding the clinical validation of novel imaging tools. As these technologies evolve, they are expected to increase diagnostic specificity, leading to more precise, patient-centered treatment approaches. Ultimately, these advancements offer substantial opportunities to transform dental practice by providing faster, less invasive, and more reliable diagnoses.

Self-regulated learning is one of the most relevant learning concepts, representing cognitive, metacognitive, emotional, behavioural and motivational aspects. The Motivated Strategies for Learning Questionnaire (MSLQ) is the most used instrument to measure self-regulated learning. Though, its 81-item structure is lengthy and presents psychometric issues. Additionally, there is no translation/validation of MSLQ for European Portuguese secondary students. This study involved two stages; in the first, the scale’s psychometric properties were examined, and a short version with 56 items was proposed; in the second, the short version was re-analysed. The first sample consisted of 795 adolescents aged 14–19; 429 adolescents formed the second sample, aged 13–17. Confirmatory factor analyses using robust estimators showed a good fit to the data for the three separated first-order models. Also, good reliability values were found, and information reproduction between the original version and this reduced proposal was verified. These results suggest that the proposed Portuguese short version of the MSLQ (MSLQ-PTS) is a valid and reliable measure for adolescent Portuguese samples. Moreover, the shorter version length makes it a more effective tool for practitioners and researchers.

This study, grounded in social identity theory, aimed to examine the mediating role of corporate reputation in the relationship between corporate social responsibility (CSR) and internal brand commitment. Additionally, it sought to investigate whether individualistic versus collectivistic cultural orientations moderate this indirect relationship. This research consisted of two complementary studies. The first study employed a qualitative approach, utilizing interviews to explore employees' perceptions of CSR practices ( N = 14). The second study adopted a quantitative approach, using an online survey to collect data from 506 participants distributed across Portugal (a collectivistic culture) and France, Italy, and Spain (characterized as individualistic cultures). The findings from the first study revealed that employees perceive CSR practices as enhancing an organization's reputation. Additionally, these practices are seen as positively influencing employees' performance, job satisfaction, and commitment by boosting their morale and strengthening their sense of organizational identification. The results from the second study showed that CSR improved employees' internal brand commitment through increases in corporate reputation. It also demonstrated that the degree of individualism or collectivism affected how employees perceived the organization's reputation and influenced their internal brand commitment. Finally, it was also shown that national culture moderated the indirect effect of CSR on internal brand commitment through corporate reputation, in such a way, that this relationship was stronger in collectivistic countries (versus individualistic). The present study contributes to reinforcing the importance of adapting CSR initiatives to the national culture, as a strategy to improve employees' commitment toward their brand.