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Understanding how humans learn by themselves is crucial to develop interventions to prevent dropout and improve learner engagement. Classical learning curves were proposed to fit and describe experimental data involving enforced learning. However in real-world learning contexts such as MOOCs and hobbies, learners may quit - and often do. Even in formal settings such as college success typically requires intensive self-study outside lectures. Previous research in educational psychology supports a positive reciprocal relationship between motivation and achievement. Integrating insights from learning curves, forgetting curves and motivation-achievement cycles, we propose a formal Reciprocal-Practice-Success (RPS) model of learning ‘in the wild'. First, we describe the different components of the basic RPS model. Using simulations, we then show how long term learning outcomes critically depend on the shape of the learning curve. Concave curves lead to more consistent learning outcomes whereas S-shaped curves lead to either expertise or dropout. We also provide a dynamical systems version for the RPS model which shows similar qualitative behaviour. Through a bifurcation analysis of two controllable learning parameters - minimum practice rate and success sensitivity, we show which learner-specific interventions may be effective to preventing dropout. We also discuss theorized mechanisms which affect the inflection point of S-shaped learning curves such as task-complexity and relative feedback from failures vs. successes. These provide more task-specific interventions to lower quitting rates. Finally, we discuss possible extensions to the basic RPS model which will allow capturing spacing effects and insights from other motivation theories.

Abstract Randomized controlled trials (RCTs) are the gold standard to establish the benefit-risk ratio of novel drugs. However, the evaluation of mature results often takes many years. We hypothesized that the addition of Bayesian inference methods at interim analysis time points might accelerate and enforce the knowledge that such trials may generate. In order to test that hypothesis, we retrospectively applied a Bayesian approach to the HOVON 132 trial, in which 800 newly diagnosed AML patients aged 18 to 65 years were randomly assigned to a “7 + 3” induction with or without lenalidomide. Five years after the first patient was recruited, the trial was negative for its primary endpoint with no difference in event-free survival (EFS) between experimental and control groups (hazard ratio [HR] 0.99, p = 0.96) in the final conventional analysis. We retrospectively simulated interim analyses after the inclusion of 150, 300, 450, and 600 patients using a Bayesian methodology to detect early lack of efficacy signals. The HR for EFS comparing the lenalidomide arm with the control treatment arm was 1.21 (95% CI 0.81–1.69), 1.05 (95% CI 0.86–1.30), 1.00 (95% CI 0.84–1.19), and 1.02 (95% CI 0.87–1.19) at interim analysis 1, 2, 3 and 4, respectively. Complete remission rates were lower in the lenalidomide arm, and early deaths more frequent. A Bayesian approach identified that the probability of a clinically relevant benefit for EFS (HR

Monoclonal neutralizing antibodies (mAbs) are considered an important prophylactic against SARS-CoV-2 infection in at-risk populations and a strategy to counteract future sarbecovirus-induced disease. However, most mAbs isolated so far neutralize only a few sarbecovirus strains. Therefore, there is a growing interest in bispecific antibodies (bsAbs) which can simultaneously target different spike epitopes and thereby increase neutralizing breadth and prevent viral escape. Here, we generate and characterize a panel of 30 novel broadly reactive bsAbs using an efficient controlled Fab-arm exchange protocol. We specifically combine some of the broadest mAbs described so far, which target conserved epitopes on the receptor binding domain (RBD). Several bsAbs show superior cross-binding and neutralization compared to the parental mAbs and cocktails against sarbecoviruses from diverse clades, including recent SARS-CoV-2 variants. BsAbs which include mAb COVA2–02 are among the most potent and broad combinations. As a result, we study the unknown epitope of COVA2–02 and show that this mAb targets a distinct conserved region at the base of the RBD, which could be of interest when designing next-generation bsAb constructs to contribute to a better pandemic preparedness.

Much research on collaborative learning focuses on working together on tasks that are designed with collaboration in mind. However, teachers may ask children to collaborate on single player tasks as well, given a scarcity of available computers in the classroom or assuming that children can learn from each other and motivate each other. In the current study, we studied the conversations of primary school children (N = 64; 39 girls, 25 boys) working together in dyads in an adaptive single-player math learning environment (Math Garden). We aimed to investigate (1) how dyads collaborate across two math tasks aimed at practicing different math skills (arithmetic vs. reasoning skills) embedded within Math Garden and (2) whether collaborative activities differed across the two math tasks. We studied both individual utterances as well as episodes of social metacognitive interactions between the dyad members. We found that children engaged in activities important for successful collaboration, such as relational and metacognitive activities. Moreover, we identified social metacognitive episodes, meaning that children regulated their groups’ learning and that the regulatory processes which took part within the collaborative learning session cannot be reduced to individual activities. We conclude that children engage in collaborative activities when working together on single player tasks. And, in line with previous research, these collaborative activities differed across games, highlighting that collaborative learning is shaped by the task at hand.

In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed errors in domains where items are susceptible to most or all causes and errors can be explained by multiple causes. We apply the model to single-digit multiplication, a domain that is very suitable for the model, is well-studied, and allows us to analyze over 25,000 error responses from 335 learners. The model, derived from the Ising model popular in physics, makes use of a bigraph that links errors to causes. The error responses were taken from Math Garden, a computerized adaptive practice environment for arithmetic that is widely used in the Netherlands. We discuss and evaluate various model configurations with respect to the ranking of recommendations and calibration of probability estimates. The results show that the SET model outranks a majority vote baseline model when more than a single recommendation is considered. Finally, we contrast the SET model to similar approaches and discuss limitations and implications.

Despite decades of extensive research on creativity, the field still combats psychometric problems when measuring individual differences in creative ability and people's potential to achieve real-world outcomes that are both original and useful. We think these seemingly technical issues have a conceptual origin. We therefore propose a minimal theory of creative ability (MTCA) to create a consistent conceptual theory to guide investigations of individual differences in creative ability. Building on robust theories and findings in creativity and individual differences research, our theory argues that creative ability, at a minimum, must include two facets: intelligence and expertise. So, the MTCA simply claims that whenever we do something creative, we use most of our cognitive abilities combined with relevant expertise to be creative. MTCA has important implications for creativity theory, measurement, and practice. However, the MTCA is not necessarily true; it is a minimal theory. We discuss and reject several objections to the MTCA.

Abstract We use longitudinal social network data from the Framingham Heart Study to examine the extent to which alcohol consumption is influenced by the network structure. We assess the spread of alcohol use in a three-state SIS-type model, classifying individuals as abstainers, moderate drinkers, and heavy drinkers. We find that the use of three-states improves on the more canonical two-state classification, as the data show that all three states are highly stable and have different social dynamics. We show that when modelling the spread of alcohol use, it is important to model the topology of social interactions by incorporating the network structure. The population is not homogeneously mixed, and clustering is high with abstainers and heavy drinkers. We find that both abstainers and heavy drinkers have a strong influence on their social environment; for every heavy drinker and abstainer connection, the probability of a moderate drinker adopting their drinking behaviour increases by $$40\%$$ 40 % and $$18\%$$ 18 % , respectively. We also find that abstinent connections have a significant positive effect on heavy drinkers quitting drinking. Using simulations, we find that while both are effective, increasing the influence of abstainers appears to be the more effective intervention compared to reducing the influence of heavy drinkers.

One of the highest ambitions in educational technology is the move towards personalized learning. To this end, computerized adaptive learning (CAL) systems are developed. A popular method to track the development of student ability and item difficulty, in CAL systems, is the Elo Rating System (ERS). The ERS allows for dynamic model parameters by updating key parameters after every response. However, drawbacks of the ERS are that it does not provide standard errors and that it results in rating variance inflation. We identify three statistical issues responsible for both of these drawbacks. To solve these issues we introduce a new tracking system based on urns, where every person and item is represented by an urn filled with a combination of green and red marbles. Urns are updated, by an exchange of marbles after each response, such that the proportions of green marbles represent estimates of person ability or item difficulty. A main advantage of this approach is that the standard errors are known, hence the method allows for statistical inference, such as testing for learning effects. We highlight features of the Urnings algorithm and compare it to the popular ERS in a simulation study and in an empirical data example from a large-scale CAL application.

Background The REDO trial (REtreatment with Rituximab in RhEmatoid arthritis: Disease Outcome after Dose Optimisation) showed similar disease activity for retreatment with ultralow doses (200 mg and 500 mg per 6 months) compared with standard low-dose rituximab (RTX, 1000 mg per 6 months). We performed an observational extension study of the REDO trial to assess long-term effectiveness.Methods Patients from the REDO trial were followed from start of the trial to censoring in April 2021. RTX use was at the discretion of patient and rheumatologist using treat to target. The primary outcome was disease activity (disease activity score in 28 joints C-reactive protein (DAS28-CRP)), analysed using a longitudinal mixed model by original randomisation and time-varying RTX dose. The original DAS28-CRP non-inferiority (NI) margin of 0.6 was used. RTX dose and persistence, safety and radiological outcomes were also assessed.Findings Data from 126 of 142 REDO patients was collected from 15 December 2016, up to 30 April 2021. Drop-outs continued treatment elsewhere (n=3) or did not consent (n=13).Disease activity did not differ by original randomisation group: 1000 mg mean DAS28-CRP (95% CI) of 2.2 (2.0 to 2.5), 500 mg 2.3 (2.1 to 2.4) and 200 mg 2.4 (2.2 to 2.5). Lower time-varying RTX dose was associated with higher DAS28-CRP (0.22 (95% CI 0.05 to 0.40) higher for 200 mg/6 months compared with 1000 mg/6 months), but remained within the NI-margin. RTX persistence was 93%. Median RTX dose was 978 mg (IQR 684–1413) per year, and no association was found between RTX dose and adverse events or radiological damage.Interpretation Long-term use of ultralow doses of RTX is effective in patients with rheumatoid arthritis responding to standard dose RTX.

Abstract Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the “ease” of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field.

Background The National Institute for Health and Care Excellence (NICE) pioneered the Health Technology Assessment (HTA) processes and methodologies. Technology appraisals (TAs) focus on pharmaceutical products and clinical and economic data, which are presented by the product manufacturers to the NICE appraisal committee for decision-making. Uncertainty in data reduces the chance of a positive outcome from the HTA process or requires a higher discount.Objective To investigate the quality of clinical data (comparator, quality of life (QoL), randomised controlled trials (RCTs) and overall quality of evidence) submitted by the manufacturers to NICE.Design This retrospective evaluation analysed active TAs published between 2000 and 2019 (up to TA600).Methods For all TAs, we extracted data from the Assessment Group and Evidence Review Group reports and Final Appraisal Determinations on (1) the quality of submitted RCTs and (2) the overall quality of evidence submitted for decision-making. For single TAs, we also extracted data and its critique on QoL and comparators. Each category was scored for quality and analysed using descriptive statistics.Results 409 TAs were analysed (multiple technology appraisals (MTA)=104, single technology appraisal (STA)=305). In two-thirds of TAs, the overall quality of evidence was either poor (n=224, 55%) or unacceptable (n=41, 10%). In 39% (n=119) of the STAs, the quality of comparative evidence was considered poor, and in 17% (n=51) unacceptable. In 44% (n=135) of STAs, the quality of QoL data was considered poor, 15% (n=47) unacceptable, 33% (n=102) acceptable and 7% (n=21) as good. Over 20 years of longitudinal analysis did not show improvements in the quality of evidence submitted to NICE.Conclusion We found that the primary components of clinical evidence influencing NICE’s decision-making framework were of poor quality. It is essential to continue to generate robust clinical data for premarket and postmarket introduction of medicines into clinical practice to ensure they deliver benefits to patients.

Abstract Background To get insight in the prevalence of high, or low/no serum infliximab trough levels in patients with low disease activity and if serum trough levels are stable and reliable longitudinally we conducted a prospective cohort study Methods In a longitudinal, observational cohort of RA patients treated with infliximab for at least 6 months, treatment interval, DAS28, infliximab trough levels and anti-infliximab antibodies were assessed. Prevalence of low (5 mg/l) infliximab serum trough levels and anti-infliximab antibodies was recorded. Relationship of a change in anti-infliximab antibodies and treatment interval was described. Reliability of consecutive infliximab serum trough levels and anti-infliximab antibodies in patients with stable DAS28 and treatment was analysed with Spearman correlation and kappa-analysis. Results 147 patients with a mean disease duration of 11 years (sd7) and DAS28 of 3.5 (sd1.3) at baseline were followed during 1.5 years. Inter-individual variability in infliximab levels in patients with low DAS28 was high (median 1.4 mg/L, IQR 3.35), with 31% (95%CI: 20-42%) having low (5 mg/L). Interestingly also in RA patients with DAS28 ≤ 3.2, anti-infliximab antibodies were found in one-third of the patients, with half of them having antibodies every visit during a median of more than one year. Agreement for consecutive measurements of serum trough levels and anti-infliximab antibodies was high in stable patients: r = 0.97 (p = 0.00001) and kappa = 1.0 (SE 0.14) Anti-infliximab antibody appearance was influenced by interval increases (relative risk (RR) 5.2, 2.6-10.7), but patients still showed low infliximab levels. Conclusions Low (and high) infliximab serum trough levels are prevalent, interestingly also in patients with low disease activity. Consecutive measurements of serum trough levels and anti-infliximab antibodies are reliable in stable patients. These test could be used to lower or stop infliximab in selected patients.

The ability to monitor and adjust our performance is crucial for adaptive behaviour, a key component of human cognitive control. One widely studied metric of this behaviour is post-error slowing (PES), the finding that humans tend to slow down their performance after making an error. This study is a first attempt at generalizing the effect of PES to an online adaptive learning environment where children practise mathematics and language skills. This population was of particular interest since the major development of error processing occurs during childhood. Eight million response patterns were collected from 150,000 users aged 5 to 13 years old for 6 months, across 23 different learning activities. PES could be observed in most learning activities and greater PES was associated with greater post-error accuracy. PES also varied as a function of several variables. At the task level, PES was greater when there was less time pressure, when errors were slower, and in learning activities focusing on mathematical rather than language skills. At the individual level, students who chose the most difficult level to practise and had higher skill ability also showed greater PES. Finally, non-linear developmental differences in error processing were found, where the PES magnitude increased from 6 to 9-years-old and decreased from 9 to 13. This study shows that PES underlies adaptive behaviour in an educational context for primary school students.

The question of how learners' motivation influences their academic achievement and vice versa has been the subject of intensive research due to its theoretical relevance and important implications for the field of education. Here, we present our understanding of how influential theories of academic motivation have conceptualized reciprocal interactions between motivation and achievement and the kinds of evidence that support this reciprocity. While the reciprocal nature of the relationship between motivation and academic achievement has been established in the literature, further insights into several features of this relationship are still lacking. We therefore present a research agenda where we identify theoretical and methodological challenges that could inspire further understanding of the reciprocal relationship between motivation and achievement as well as inform future interventions. Specifically, the research agenda includes the recommendation that future research considers (1) multiple motivation constructs, (2) behavioral mediators, (3) a network approach, (4) alignment of intervals of measurement and the short vs. long time scales of motivation constructs, (5) designs that meet the criteria for making causal, reciprocal inferences, (6) appropriate statistical models, (7) alternatives to self-reports, (8) different ways of measuring achievement, and (9) generalizability of the reciprocal relations to various developmental, ethnic, and sociocultural groups.

Abstract Background Immunization of pregnant women with a tetanus-diphtheria-and-acellular-pertussis (Tdap) vaccine is an effective and safe way to protect infants from pertussis before their primary vaccinations. Vaccine uptake among pregnant women is influenced by their care providers’ attitudes toward maternal vaccination. This qualitative study aimed to evaluate the implementation of the maternal Tdap vaccination under the National Immunization Program of the Netherlands from the perspective of obstetric care providers. Methods In this qualitative and explorative study, we conducted in-depth interviews by telephone with obstetric care providers who were selected from a pool of respondents (convenience sampling) to a questionnaire in a previous study. The interviews were based on a semi-structured interview guide that covered three aspects of the implementation strategy: providers’ overall experience with the implementation of maternal Tdap vaccination in the Netherlands; implementation logistics and counseling, and pregnant women referrals to municipal Youth Healthcare Centers. The interviews were recorded, pseudonymized and transcribed verbatim. Transcripts were analyzed according to the Thematic Analysis approach by two researchers independently in two phases of iterative coding, categorizing, reviewing and redefining until ultimately, emergent themes regarding maternal Tdap vaccination implementation were identified. Results Interviews with 11 midwives and 5 OB-GYN physicians yielded 5 major themes regarding the Tdap vaccination implementation strategy: challenges throughout the implementation process, views on maternal Tdap vaccination, general versus tailored counseling, provider responsibilities in vaccine promotion, and impact of materials for information delivery. Participants indicated that to improve provider attitudes toward Tdap vaccination, its implementation requires clear and transparent information about what is entailed, i.e., what is expected from obstetric care providers, how they can obtain information, and when their actions must be initiated. Participants demanded involvement throughout the implementation planning process. They preferred tailored communication with pregnant women over a generalized approach. Conclusion This study emphasized the importance of involving all relevant healthcare professionals in planning the implementation of maternal Tdap vaccination. Possible barriers perceived by these professionals should be taken into account in order to improve their attitudes toward vaccination, thus to increase uptake among pregnant women.

Background and Context: Valid assessment of understanding of programming concepts in primary school children is essential to implement and improve programming education. Objective: We developed and validated the Computerized Adaptive Programming Concepts Test (CAPCT) with a novel application of Item Response Theory. The CAPCT is a web-based and resource-efficient adaptive assessment of 4489 questions measuring: the understanding of basic sequences, loops, conditions (if & if-else statements), debugging, multiple agents, procedures, and the ability to generalize to a new syntax. Method: Data was collected through an existing online adaptive practice and monitoring system called Math Garden. We collected 14 million responses from 93,341 Dutch children (ages 4-13). Findings: The CAPCT demonstrated good psychometric qualities because 75% of the variance in question difficulty was explained by differences in item characteristics. The CAPCT demonstrated robustness against adding new participants and adding new items. Differences in player ability (i.e., understanding of CS concepts) were due to differences in age, gender, the number of items played, and prior mathematical ability. Implications: The CAPCT may be used by teachers to identify the level of programming concept understanding of their pupils, while researchers may use the CAPCT to construct and validate effective teaching resources.

With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion responses. We present the methods we use to both steer and analyze this system in real-time, using scoring rules on accuracy and response times, a tailored rating system to provide both learners and items with current ability and difficulty ratings, and an adaptive engine that matches learners to items. Moreover, we explore the quality of fit by means of prediction accuracy and parallel item reliability. Limitations and pitfalls are discussed by diagnosing sources of misfit, like violations of unidimensionality and unforeseen dynamics. Finally, directions for development are discussed, including embedded learning analytics and a focus on online experimentation to evaluate both the system itself and the users' learning gains. Though many challenges remain open, we believe that large steps have been made in providing methods to efficiently manage and research educational big data from a massive online learning system.

Introduction Maternal vaccination is a promising strategy to reduce the burden of vaccine-preventable diseases for mothers and infants. We aimed to provide an up-to-date overview of the efficacy and safety of all available maternal vaccines.Methods We searched PubMed, Embase, CENTRAL and ClinicalTrials.gov on 1 February 2022, for phase III and IV randomised controlled trials (RCTs) that compared maternal vaccination against any pathogen with placebo or no vaccination. Primary outcomes were laboratory-confirmed or clinically confirmed disease in mothers and infants. Secondary safety outcomes included intrauterine growth restriction, stillbirth, maternal death, preterm birth, congenital malformations and infant death. Random effects meta-analysis were used to calculate pooled risk ratio’s (RR). Quality appraisal was performed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE).Results Six RCTs on four maternal vaccines, influenza, tetanus, diphtheria and pertussis (Tdap), pneumococcal and respiratory syncytial virus (RSV) were eligible. The overall risk of bias and certainty of evidence varied from low to high. Maternal influenza vaccination significantly reduced the number of laboratory-confirmed influenza cases (RR 0.58, 95% CI 0.42 to 0.79, event rate 57 vs 98, 2 RCTs, n=6003, I2=0%), and clinically confirmed influenza cases in mothers (RR 0.88, 95% CI 0.78 to 0.99, event rate 418 vs 472, 2 RCTs, n=6003, I2=0%), and laboratory-confirmed influenza in infants (RR 0.66, 95% CI 0.52 to 0.85, event rate 98 vs 148, 2 RCTs, n=5883, I2=0%), although this was not significant for clinically confirmed influenza in infants (RR 0.99, 95% CI 0.94 to 1.05, event rate 1371 vs 1378, 2 RCTs, n=5883, I2=0%). No efficacy data were available on maternal Tdap vaccination. Maternal pneumococcal vaccination did not reduce laboratory-confirmed and clinically confirmed middle ear disease (RR 0.49, 95% CI 0.24 to 1.02, event rate 9 vs 18, 1 RCT, n=133 and RR 0.88 95% CI 0.69 to 1.12, event rate 42 vs 47, 1 RCT, n=133, respectively), and clinically confirmed lower-respiratory tract infection (LRTI) (RR 1.08, 95% CI 0.82 to 1.43, event rate 18 vs 34, 1 RCT, n=70) in infants. Maternal RSV vaccination did not reduce laboratory-confirmed RSV LRTI in infants (RR 0.75, 95% CI 0.56 to 1.01, event rate 103 vs 71, 1 RCT, n=4527). There was no evidence of a significant effect of any of the maternal vaccines on the reported safety outcomes.Conclusions The few RCTs with low event rates suggest that, depending on the type of maternal vaccine, the vaccine might effectively prevent disease and within its size does not show safety concerns in mothers and infants.PROSPERO registration number CRD42021235115.

Glucose-derived isosorbide is a rigid polyester monomer with a low reactivity. Here, the authors report the synthesis of high molecular weight biobased polyesters with promising barrier and mechanical properties via in situ generation of reactive aryl ester groups.

Abstract Prior research into the relationship between attitudes and vaccination intention is predominantly cross-sectional and therefore does not provide insight into directions of relations. During the COVID-19 vaccines development and enrollment phase, we studied the temporal dynamics of COVID-19 vaccination intention in relation to attitudes toward COVID-19 vaccines and the pandemic, vaccination in general, social norms and trust. The data are derived from a longitudinal survey study with Dutch participants from a research panel (N = 744; six measurements between December 2020 and May 2021; age 18–84 years [M = 53.32]) and analyzed with vector-autoregression network analyses. While cross-sectional results indicated that vaccination intention was relatively strongly related to attitudes toward the vaccines, results from temporal analyses showed that vaccination intention mainly predicted other vaccination-related variables and to a lesser extent was predicted by variables. We found a weak predictive effect from social norm to vaccination intention that was not robust. This study underlines the challenge of stimulating uptake of new vaccines developed during pandemics, and the importance of examining directions of effects in research into vaccination intention.

Objectives While protection against pertussis following maternal tetanus-diphtheria-and-acellular-pertussis (Tdap) vaccination was demonstrated in healthy term-born infants, no evidence is available on Tdap vaccination in combination with immune-modulating therapy during pregnancy. In this pilot study, we explored whether treatment with tumour necrosis factor alpha inhibitors (TNFis) in pregnant patients with rheumatic disease interferes with Tdap vaccine responses and affects maternal anti-pertussis IgG antibody levels in newborns.Methods Patients were included by a rheumatologist during pregnancy in case they received maternal Tdap vaccination in the late-second or early-third trimester of pregnancy. Blood samples were obtained from mothers during the first pregnancy trimester, 3 months after delivery and from the umbilical cord. IgG antibody levels against Tdap-included antigens were measured using a bead-based multiplex immunoassay. Findings on patients exposed to TNFis were compared with those from TNFi-unexposed patients and with data from a historical comparator study among healthy Tdap vaccinated mother–infant pairs (n=53).Results 66 patients (46 exposed and 20 unexposed to TNFIs) were enrolled. No major differences in IgG antibody levels were observed between TNFi-exposed and unexposed mothers before maternal Tdap vaccination and 3 months after delivery. In cord sera, however, antibody levels against pertussis toxin were significantly lower after TNFi-treatment (35.94 IU/mL, 95% CI 20.68 to 62.45) compared with no TNFi-treatment of mothers with rheumatic disease (94.61 IU/mL, 95% CI 48.89 to 183.07) and lower compared with a cohort of healthy mothers (125.12 IU/mL, 95% CI 90.75 to 172.50). We observed similar differences for filamentous haemagglutinin, pertactin, tetanus toxoid and diphtheria toxoid.Conclusion These preliminary data indicate no major differences in IgG antibody levels on maternal Tdap vaccination in pregnant women with or without immune-modulating treatment, although our findings suggest that TNFis during pregnancy induce lower maternal anti-pertussis-specific protective antibody levels in newborns.

Pharmaceutical residues end up in surface waters, impacting drinking water sources and contaminating the aquatic ecosystem. Pharmacists can play a role in reducing pharmaceutical residues, yet this is often not addressed in pharmacy undergraduate education. Therefore, we developed the educational module “Reducing Pharmaceuticals in Water” for pharmacy students; this was integrated in our pharmacy simulation game for third year Master of Pharmacy students at the University of Groningen. In this study, we aim to evaluate the effects of the module on students’ knowledge of pharmaceutical residues in water, to describe students’ experiences in taking the module, and to explore their attitudes towards green pharmacy education in general. This mixed-methods study included quantitative measurements, before and after students took the module (intervention group) and in a control group which did not receive the module. Data were collected between February 2023 and June 2023. Overall, 29 students took the module and 36 students were in the control group. The knowledge score of students in the intervention group (N = 29) increased significantly from 9.3 to 12.9 out of 22 (p < 0.001). The knowledge score of the students in the control group was (8.9 out of 22). Students found the e-learning and the patient cases the most exciting part of this module. Students also recognized the need to including environmental issues in pharmacy education. In conclusion, the module contributes towards improved knowledge and increased awareness of the impact of pharmaceuticals found in water. It represents a promising strategy to strengthen pharmacist’s role in mitigating the amount and the effect of pharmaceuticals on water and the environment in the future.

Worldwide, including Indonesia and the EU, current (agricultural) use in peatlands is based on massive water drainage. Because drainage leads to environmental problems, many scholars, policy makers and (agricultural) entrepreneurs are rethinking peatland use, aiming for more sustainable peatland management, based on rewetting. However, policymakers and governments often hesitate to implement measures in practice, because rewetting peatlands could have massive socio-economic impacts. Serious Gaming (SG) can facilitate the transition to more sustainable use of peat areas because it provides a safe environment in which social and physical impact of choices can be simulated and evaluated. The SG website http://peatland.eu/ aims to contribute to transition processes for sustainable futures by exploring processes of communication, participation, and social-ecological learning in peatland initiatives. Envisioning a similar impact of this virtual Living Lab it is the ambition to design http://peatland.asia/ and thereby provide a learning strategy for Higher Education Institutes and other interested parties. Achieving such strategy requires a transdisciplinary approach to meet user experience and interface requirements, scientific validity, and contemporary relevance. This paper explores both websites in a context of a collaborative initiative to engage a diversity of peatland colleagues in the further development of interactive relevance of the website.