Amsterdam Institute for Addiction Research

Digitalization in geriatric rehabilitation presents unique challenges, making it essential to align eHealth solutions with patients' digital skills. The Quickscan Digital Skills (QDS) is a tool designed to help health care professionals match eHealth interventions to individual skill levels. This study aimed to explore the applicability of QDS by comparing it to self-reported digital skills and to gain insight into the digital skills of patients in geriatric rehabilitation. In this multicenter cross-sectional study, participants from 13 geriatric rehabilitation centers in the Netherlands completed a survey, including demographic questions, QDS, and a numeric rating scale (NRS) for self-reported digital skills. Participants were categorized into 3 skill levels (beginner, intermediate, and experienced) based on the cutoff points in QDS scores. Cutoff points were predetermined, guided by the information provided on QDS. Descriptive statistics for median age and frequencies for skill levels were calculated. Comparative analysis using a Kruskal-Wallis test assessed differences between QDS and NRS within these groups, and Spearman rank-order correlation examined the relationship between the two measures. To gain more insight into the different skill levels between groups, data were visualized and associations among age, gender, and digital skill levels were examined using ordinal logistic regression analysis. A total of 463 patients (median age 78, IQR 12 years; 282/463, 60.9% female) participated in this study. Based on QDS scores, 42.1% (195/463) were classified as beginners, 19.4% (90/463) as intermediates, and 38.4% (178/463) as experienced users. A moderate positive correlation was found between QDS and NRS scores. Digital skills generally declined with age: 69.8% (37/53) of participants younger than 65 years were experienced users compared to only 13.2% (5/38) of those older than 91 years. A logistic regression analysis showed that increasing age was significantly associated with lower digital skill levels (odds ratio 0.93, 95% CI 0.92-0.95; P<.001). The association between age and digital skills does not differ between males and females. This study suggests that QDS is a promising and practical screening tool for assessing digital skills in patients in geriatric rehabilitation. Self-reported digital skills with an NRS do not capture the differentiation in the assessed abilities by QDS. QDS could be a practical tool for identifying digital skill levels in patients in geriatric rehabilitation and can support more personalized eHealth implementation. Further research should explore the parametric properties of QDS and how the scores relate to actual eHealth use.

Thiopurines are used to maintain remission in inflammatory bowel disease (IBD). These drugs are metabolized into 6-thioguanine nucleotides (6-TGN), associated with efficacy, and 6-methylmercaptopurine ribonucleotides (6-MMPR), associated with adverse drug reactions. Pregnancy has been linked to a shift in thiopurine metabolism, characterized by reduced 6-TGN and increased 6-MMPR levels. The clinical impact of these changes remains unclear. To explore the association between changes in 6-TGN and 6-MMPR levels with disease activity and toxicity markers in women with IBD during pregnancy. This retrospective cohort study included pregnant women with IBD who used thiopurines from six Dutch hospitals (2017-2022). Linear mixed-effects models were used to model changes of 6-TGN and 6-MMPR before, during and after pregnancy, and to identify associations with markers of disease activity (faecal calprotectin) and toxicity (alanine aminotransferase [ALT], leukocytes, platelets). A total of 87 women with 100 pregnancies were included (64.4% Crohn's disease, 32.2% ulcerative colitis). A significant reduction in 6-TGN was found in the second and third trimester, but no associations with changes in faecal calprotectin were detected. There were no significant increases in 6-MMPR. Increases in 6-MMPR were associated with modest elevations in ALT, but none of the other toxicity markers. Transient thrombocytopenia and leukopenia occurred thrice, and elevated liver enzymes were observed in nine pregnancies. Although 6-TGN levels decreased during pregnancy, these fluctuations were not associated with increased disease activity or toxicity. No significant increase in 6-MMPR levels was observed. Proactive monitoring may therefore not be warranted in the pregnant population.

Curcumin exhibits anti-inflammatory properties, but clinical evidence is limited, in part because of its low systemic bioavailability. Nevertheless, its limited absorption may favor local activity in the gut, where it could influence inflammatory bowel disease via microbiota modulation. This study assesses the impact of curcumin on gut microbiota diversity, as well as clinical and biochemical parameters in patients with ulcerative colitis, and Crohn’s disease in remission and healthy individuals. In a single-center, open-label, single-arm study, 29 male participants aged 18–65 were included. Participants received 3 g of curcumin twice daily for 8 weeks. Blood, urine, and fecal samples were collected at baseline, 4 weeks, and 8 weeks. Clinical and biochemical parameters, along with curcumin plasma, urine, and fecal concentrations, were assessed. Microbiome diversity was analysed using 16 S rRNA amplicon sequencing. The study was registered in the Dutch Clinical Trial Register with ID NL8770. Twenty-nine participants completed the study. Curcumin was well tolerated with stable clinical scores (SSCAI ≤ 2, HBI ≤ 5). Plasma levels were near the lower limit of quantification, while fecal levels were markedly higher. No significant changes in alpha-diversity were found. A temporary shift in beta-diversity appeared at 4 weeks but reversed by week 8. Curcumin caused only transient microbiota changes and slight alterations in taxa abundance, suggesting limited potential for sustained microbiota modulation in IBD management. Clinical trial registration: The study was registered in the Dutch Clinical Trial Register with ID NL8770.

Early life is a critical window for immune system development, during which the gut microbiome shapes innate immunity, antigen presentation, and adaptive immune maturation. Disruptions in microbial colonization—driven by factors such as cesarean delivery, antibiotic exposure, and formula feeding—deplete beneficial early-life taxa (e.g., Bifidobacterium, Bacteroides, and Enterococcus) and impair key microbial functions, including short-chain fatty acid (SCFA) production by these keystone species, alongside regulatory T cell induction. These dysbiosis patterns are associated with an increased risk of pediatric autoimmune diseases, notably type 1 diabetes, inflammatory bowel disease, celiac disease, and juvenile idiopathic arthritis. This review synthesizes current evidence on how the early-life microbiota influences immune maturation, with potential effects on the development of autoimmune diseases later in life. We specifically focus on human observational and intervention studies, where treatments with probiotics, synbiotics, vaginal microbial transfer, or maternal fecal microbiota transplantations have been shown to partially restore a disrupted microbiome. While restoration of the gut microbiome composition and function is the main reported outcome of these studies, to date, no reports have disclosed direct prevention of autoimmune disease development by targeting the early-life gut microbiome. In this regard, a better understanding of the early-life microbiome–immune axis is essential for developing targeted preventive strategies. Future research must prioritize longitudinal evaluation of autoimmune outcomes after microbiome modulation to reduce the burden of chronic immune-mediated diseases.

ABSTRACT Creating effective policies for sustainable development remains a pressing challenge for emerging economies, where rapid growth often collides with environmental concerns. This study investigates the role of renewable energy (RE), foreign direct investment (FDI), natural resource use, economic growth (GDP), and education (ED) in shaping carbon dioxide (CO 2 ) emissions across E‐7 countries from 1990 to 2024. Using advanced panel econometric techniques, including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and the Pooled Mean Group Autoregressive Distributed Lag (PMG‐ARDL) model, the analysis provides robust long‐run estimates while addressing potential endogeneity. The results show that RE and ED significantly mitigate CO 2 emissions, reducing them by 0.59% and 0.24%, respectively, whereas FDI inflows and natural resource exploitation increase emissions by 2.6% and 2.93%. GDP displays mixed impacts consistent with the Environmental Kuznets Curve (EKC) hypothesis. Causality outcomes reveal complex bidirectional linkages among RE, ED, GDP, and emissions, underscoring the interconnected nature of development and environmental outcomes. By highlighting the dual role of FDI and integrating education and renewable energy within the EKC framework, this study contributes to the literature on sustainable pathways for emerging economies. The findings suggest that prioritizing investment in renewable energy and human capital is essential for the E‐7 countries to reconcile growth objectives with their commitments to the Sustainable Development Goals (SDGs).

Anelloviruses are omnipresent in the human population, yet their transmission routes, especially in early life, remain unclear. This study focused on compartmentalization between blood and the mammary gland to investigate the likelihood of virus transmission via milk. We show that serum and milk samples generally share anellovirus genera and lineages. Interestingly, serum as well as milk samples collected between 2 and 6 months postpartum tested mainly negative for anelloviruses, but those received thereafter were dominated by beta- and gammatorquevirus, reflecting the initial anellovirus colonizers observed in children.

BackgroundApplication of standard infection prevention and control (IPC) measures is crucial to prevent hospital-acquired infections, but compliance by physicians is suboptimal. Interventions aimed to improve compliance are often generic and lack sustained effects. A better understanding of physicians’ trade-offs regarding application of IPC and influences on their behavior is needed to develop effective behavior change interventions. We aimed to understand physicians’ decision-making processes around application of IPC and the factors that influence their behavior.MethodsThis qualitative study involved semi-structured interviews with 18 physicians and 7 nurses from five different hospitals in the Netherlands. Reflexive thematic analysis involved inductive coding followed by deductive analysis using mechanisms of action, including the Theoretical Domains Framework, that link to behavior change techniques.ResultsWe found heterogeneity in physicians’ approaches to decision-making around application of IPC. Some physicians relied on heuristics, while others applied logical reasoning. The latter group made an autonomous assessment of the risks for infection associated with a situation and traded off the costs and benefits of IPC application. The decision was further influenced by personal beliefs about the value of IPC and a supporting physical and social environment. Eighteen out of 26 mechanisms of action underlying the influences on IPC behavior were matched to our results; most important are “memory, attention and decision processes”, “behavioral cueing”, “beliefs about consequences”, “values”, “norms”, “social influences”, “social learning/imitation” and “environmental context and resources”. These findings suggest that interventions are most likely to be beneficial if these focus on developing heuristics, changing risk beliefs, using social norms and imitation and generating a supportive environment.ConclusionThe heterogeneity in physicians’ decision-making and autonomous risk assessment which is different from other healthcare professionals calls for tailored interventions targeting heuristic decision making, personal beliefs, social norms and the environmental context.

ABSTRACTAn estimated 10% of coronavirus disease (COVID‐19) survivors suffer from persisting symptoms referred to as long COVID (LC), a condition for which approved treatment options are still lacking. This systematic review (PROSPERO: CRD42024499281) aimed to explore the pathophysiological mechanisms underlying LC and potential treatable traits across symptom‐based phenotypes. We included studies with primary data, written in English, focusing on omics analyses of human samples from LC patients with persistent symptoms of at least 3 months. Our search in PubMed and Embase, conducted on January 8, 2024, identified 642 studies, of which 29 met the inclusion criteria after full‐text assessment. The risk of bias was evaluated using the Joanna Briggs Institute appraisal tool. The synthesis of omics data, including genomics, transcriptomics, proteomics, metabolomics, and metagenomics, revealed common findings associated with fatigue, cardiovascular, pulmonary, neurological, and gastrointestinal phenotypes. Key findings included mitochondrial dysfunction, dysregulated microRNAs associated with pulmonary dysfunction, tissue impairment, blood–brain barrier disruption, coagulopathy, vascular dysfunction, microbiome disturbances, microbial‐derived metabolite production and persistent inflammation. Limitations include cross‐study heterogeneity and variability in sampling methods. Our review emphasizes the complexity of LC and the need for further longitudinal omics‐integrated studies to advance the development of biomarkers and targeted treatments.

Cigarette smoking poses a major public health risk, requiring scalable and accessible interventions. Chatbots offer a promising solution, given their potential in providing personalized, long-term interactions. Despite their promise, limited research has examined their efficacy and the intertwined relationship between user experience and effectiveness over an extended period of time. In this prospective, single-arm study, we developed and evaluated Roby, a 5-session chatbot intervention incorporating motivational interviewing and cognitive behavioral therapy to help smokers quit. Roby engaged Dutch adult smokers (N=102) in conversations covering topics such as setting a quit date, managing withdrawal and cravings, and relapse prevention. The primary outcome was the continuous abstinence rate at the end of the intervention, and secondary outcomes included 7-day point prevalence abstinence, self-efficacy, and cravings. User engagement, therapeutic alliance, and interaction satisfaction were measured weekly, and the trajectory was analyzed using Linear Mixed Models. Following an intention-to-treat principle, 18.6% of participants achieved continuous abstinence, and 37.3% achieved 7-day point prevalence abstinence. Self-efficacy significantly improved over the intervention, and cravings decreased over time. A slight decreasing trend was observed in engagement and satisfaction, likely due to a novelty effect. However, the decrease did not affect the intervention's outcomes. This study demonstrates the feasibility and initial usefulness of Roby, highlighting the potential for chatbots in long-term cessation support. Future research should further validate these findings with randomized controlled trials. Additional efforts should focus on monitoring and maintaining user experience in the long term to enhance effectiveness.