Unlabelled: This study explored associations between group memberships and recovery capital amongst 20 young adults aged 18 to 21 years in residential alcohol and drug treatment.
Method: Participants completed an interviewer administered research interview based on measures of recovery capital and a social networks assessment mapping group memberships, group substance use, and relationships between groups.
Results: Higher personal and social recovery capital was associated with lower diversity of group memberships, a higher number of positive links between groups, and greater compatibility of lower substance-using groups with other groups in the network. Higher compatibility of heavier-using groups was also associated with having a higher number of negative, antagonistic ties between groups.
Conclusions: These findings indicate that it is higher compatibility of a lower substance-using social identity and lower-using group memberships that contributes to recovery capital. Further, positive ties between groups and lower diversity of group memberships appear to be key aspects in how multiple social identities that are held by young adults relate to personal and social recovery capital.
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http://dx.doi.org/10.1016/j.abrep.2016.10.002 | DOI Listing |
PLoS One
January 2025
Division of Hepatobiliary and Transplantation Surgery, Department of Surgery, Erasmus MC Transplant Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Background And Objectives: Urological complications after kidney transplantation, due to the ureteroneocystostomy, are associated with significant morbidity, prolonged hospital stay and even mortality. Ureteral stents can minimize the number of complications but are not consistently used, as previous studies were retrospective in nature. We aim to prospectively determine the most effective stenting approach.
View Article and Find Full Text PDFWater Sci Technol
January 2025
Engineering & Energy, College of Science Health Engineering and Education, Murdoch University, 6150 Perth, Australia E-mail:
Biogas, consisting mainly of CO and CH, offers a sustainable source of energy. However, this gaseous stream has been undervalued in wastewater treatment plants owing to its high CO content. Biogas upgrading by capturing CO broadens its utilisation as a substitute for natural gas.
View Article and Find Full Text PDFPsychol Rep
January 2025
Department of Psychology, West University of Timișoara, Timișoara, România.
In contemporary, high-speed work settings, ensuring the well-being of employees is of paramount importance. The current study builds on this concern about employee well-being and aims to explore the complex connection between workload (as a job demand), micro-breaks (as behavioral resources), and psychological capital (PsyCap; as a personal resource) to understand their impact on end-of-day well-being. A daily diary approach was employed, where employees provided data from Monday to Friday throughout a workweek.
View Article and Find Full Text PDFFront Public Health
January 2025
School of Politics and Public Administration, Guangxi Minzu University, Nanning, Guangxi, China.
Introduction: The non-emergency transfer multi-level protection system is a pivotal livelihood endeavor in China, serving as a vital diversified component within the robust framework of a Chinese-style modern social security system. This system faces various challenges, including displacement of emergency capacity by non-emergency demands, uneven allocation of transfer resources, service quality variations, inadequate management structures, limited regulatory frameworks, and social acceptance issues.
Methods: Leveraging structural theory, this study analyzes the primary issues in the current implementation of China's non-emergency transfer security system.
Water Res
January 2025
Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK; SWING - Department of Built Environment, Oslo Metropolitan University, St Olavs plass 0130, Oslo, Norway. Electronic address:
Climate resilience in water resource recovery facilities (WRRFs) necessitates improved adaptation to shock-loading conditions and mitigating greenhouse gas emission. Data-driven learning methods are widely utilised in soft-sensors for decision support and process optimization due to their simplicity and high predictive accuracy. However, unlike for mechanistic models, transferring machine-learning-based insights across systems is largely infeasible, which limits communication and knowledge sharing.
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