Acquiring generic knowledge without induction in infancy.

Children are ecological learners; they adapt their information search strategies to fit the structure of their immediate learning environment. In two studies, we explore whether this search behavior is impacted by the potential for later information gain. In Experiment 1, 60 5-9-year-olds were presented with a population of different colored balls with a hidden property and a sample that was either representative or unrepresentative of that population. Children were asked to select a tool that would allow them to learn about the hidden property: one tool yielded more information from the local set of sampled items, while the other yielded more information about the global population. We find that, regardless of age, children consistently choose the most effective tool to support global information gain. In Experiment 2, we assessed whether this choice was truly motivated by the tool's potential to support learning that goes beyond the immediate sample (i.e., global yield), or due to children's reliance on another strategy (i.e., tool versatility or set ratios). To test this, we included 151 7-14-year-olds and 34 adults. In all conditions, participants were presented with a choice between learning tools that pitted global yield against an alternate strategy. We found that both children and adults consider global yield when selecting a tool, a tendency that increases with age. Children also consider the versatility of the tool when planning for downstream learning opportunities. We discuss the implications of these findings for understanding how learners develop strategies for prioritizing the acquisition of generalizable knowledge. SUMMARY: Children choose information-gathering tools by balancing immediate usefulness with the potential for broadly informative learning. By age five, children use sample representativeness to guide prospective choices about how to learn. Younger children often rely on tool versatility, whereas older learners increasingly prioritize tools that support broader inference. Development reflects shifts in epistemic strategy use rather than convergence on a single optimal approach to information search.

Chicken feet reimagined: A strategic platform for nutritional innovation, industrial valorization, and academic-industry synergies.

This critical discussion paper argues that the development of nurse-sensitive metrics in general practice is not simply a technical task of selecting indicators, but an ethical and methodological process through which nursing contribution becomes known, named and represented. Although health systems increasingly prioritise measurement, accountability and performance data, important dimensions of nursing practice remain poorly captured, particularly in community and primary care contexts. In general practice, nursing care is characterised by generalist, relational, preventive and cumulative forms of care, making the direct transfer of metrics developed outside this context problematic. General practice nurses represent a substantial workforce, yet their contribution remains only partially visible within existing healthcare data systems. This paper advances a Responsible Action Research approach to developing nurse-sensitive metrics grounded in everyday practice. Drawing on Action Research, implemented through Appreciative Inquiry and informed by the Quality Action Research Checklist, the paper considers how collaborative inquiry can support general practice nurses to articulate dimensions of nursing quality that may otherwise remain tacit. Inclusion of perspectives from general practitioners, patients and practice administrators further situates this inquiry within the broader ecology of care. The paper argues that responsible metric development requires attention not only to what is eventually measured, but to the transparency, reflexivity and accountability of the process through which potential indicators are generated. By reframing metric development as a practice-engaged process of knowledge generation, it offers a methodological contribution to debates on how nursing work can be made visible without reducing its complexity.

Depression is a common mental health disorder which frequently co-occurs with increased body mass index or increased waist circumference (hereafter 'overweight'), causing heightened cardiovascular risk. Unhealthy lifestyle behaviours underlie both conditions. The Multimodal Lifestyle Intervention (MLI) LEEF integrates physical activity, nutrition, and behavioural strategies, tailored to motivational challenges common in depression, offering a dual focus on mental and physical health. However, unpublished process data revealed very limited referral to MLI‑LEEF from both primary and secondary care, and consequently low initiation rates, signalling clear implementation challenges. This study addresses this gap by translating prioritised implementation determinants into conceptually and empirically grounded implementation strategies and examining what works, how, and under which conditions. This quasi‑experimental, explanatory sequential mixed‑methods study will implement MLI‑LEEF across ten general practices and three secondary mental health care outpatient clinics in the Northern Netherlands. Implementation strategies will be developed and tailored using Causal Pathway Diagramming and applied over a six‑month period. Quantitative data will be collected before, during, and after implementation to assess proximal implementation outcomes (the immediate, observable effects of an implementation strategy), distal implementation outcomes (adoption and sustainability), service‑level penetration, and patient outcomes. Following the implementation period, semi‑structured interviews will be conducted with referrers from each participating organisation. Site‑specific topic guides, informed by each organisation's implementation plan, causal pathway diagrams, and quantitative implementation outcomes, will probe how strategies generate change (mechanisms), how they influence targeted determinants, and which contextual conditions (preconditions, moderators) shape implementation strategy functioning. This study will respond to fieldwide calls in implementation science for rigorous, transparent, and context-sensitive approaches to developing and evaluating implementation strategies. By examining how strategies shape referral and initiation in routine general practice and specialist mental health services, and by clarifying the mechanisms and contextual conditions under which they are effective, the study will generate actionable insight into why implementation succeeds or falters in real-world care. These insights will provide essential groundwork for strengthening the reach and adoption of MLI-LEEF and will offer transferable guidance for embedding multimodal lifestyle interventions into everyday care, while advancing generalizable knowledge of how implementation strategies produce change. 10.17605/OSF.IO/XJHCB.

Human biological samples are a valuable source of information that may aid in the generation of new knowledge. However, the use of human biological samples for research poses various ethical, legal and social issues (ELSI). We performed a scoping review to identify the ethical issues surrounding the use of human biological samples for research. We developed a search string strategy to identify literature in PubMed, Scopus, Web of Science, and Google Scholar. Out of 4067 identified articles, 61 articles were included for final analysis. The findings of this study revealed multiple ethical issues stemming from the knowledge and awareness of different stakeholders involved in research, the factors affecting donors' study participation, the consent process, and the governance and structures of these human biological samples. This study will provide guidance for researchers, IRB members, and other stakeholders involved in the ethical consideration of using human biological samples for secondary research.

The project Aging in Place applies a novel approach to investigate how social care services in Sweden are adapted to preferences and needs of older persons (65 years and older) living at home with dementia, including their partners. The project covers the process that starts when a person is granted to receive services, which are communicated to a care provider – who should organize the services – and finally reach the receiving older person. This approach differs from previous research on elder care, which has focused either on the purchaser or the provider side of Swedish municipal elder care in the purchaser-provider model Sweden adopted since the mid-1990s. The project focuses on: 1) what specific social care services older persons living at home with dementia are granted; if a dementia diagnosis is needed for some services; and the differences between municipalities; 2) how care providers organise granted services and adapt them to people living with dementia; including differences between municipalities and care provider units; 3) how care recipients living with dementia (including co-habiting partners) experience and influence the receiving of services. The ambition is to generate both generalisable knowledge about social care services for people living with dementia in Sweden, including differences between municipalities and care providers, and in-depth, exploratory knowledge about how care providers organise services and how these services are received by care recipients. The project encompasses a necessary combination of methods and materials: register studies, web surveys, as well as observations and interviews. The project will provide important, elemental, knowledge on Swedish dementia- and eldercare. This knowledge is needed as a basis for further studies and as a contribution to discussions on how future social care can be developed to ensure people living with dementia, and their partners, equality, participation, and dignity in later life.

Artificial Intelligence in Biomedical Scientific Publishing.

Evaluate whether large language models reason or simply regurgitate training data in clinical diagnosis. We audited 2000 clinical case reports from PubMed Central: 1000 from 2021 to 2022 (within training data) and 1000 from 2025 (after training cutoffs). Five frontier LLMs generated diagnoses evaluated by an independent AI judge validated against physician consensus (n = 10 000 evaluations). Diagnostic accuracy was virtually identical across temporal cohorts (66.8% contaminated vs 66.9% clean), directly contradicting the memorization hypothesis. Lexical similarity was uniformly low (mean ROUGE-L 0.057), and semantic similarity measured by BERTScore showed no memorization signal (F1 0.8182 contaminated vs 0.8195 clean, Δ = +0.0013), confirming that models generate novel reasoning rather than regurgitating training data. This large-scale audit, using both lexical and semantic similarity metrics, provides compelling evidence that LLMs engage in genuine clinical reasoning rather than regurgitating memorized training data. Models demonstrated equivalent accuracy on cases they could not have seen during training, suggesting they have internalized generalizable medical knowledge rather than memorizing specific cases.

Many participants are motivated to enroll in clinical trials both for the prospect of individual benefit and for altruistic reasons. When a clinical trial is stopped early, it may significantly alter the participant trial experience and impact the likelihood that the trial will contribute to generalizable knowledge. Despite the frequency with which trials are stopped early, occurring in ten to thirty percent of trials, participants are rarely informed of this possibility during the informed consent process. Therefore, they are not given the opportunity to take this into consideration in their decision-making process. To redress this, we advance a framework for disclosing the possibility of early trial termination to prospective participants, arguing that disclosure is justified because it supports participant decision-making and promotes transparency and trust in the research enterprise.

ABSTRACT Global citizen science platforms open up participation in science to many people across the world. However, they frame participation around producing data for professional scientists. This raises the question of whether and how global citizen science affects epistemic diversity in scientific research. I address this question using a case study of the global birdwatching platform eBird as it has been taken up in India. Based on results from a qualitative empirical study, I argue that eBird does provide some opportunities for the diverse and local interests, needs, and practices of birdwatchers to impact on the generation of scientific knowledge about birds. Global citizen science therefore can to some extent increase epistemic diversity.

ABSTRACT This study advances participatory qualitative inquiry by engaging children as co-researchers in analyzing data about urban life and city design. Grounded in participatory action research and a mosaic approach, the project drew on the 7th Report on Childhood and Adolescence in (2021–2023) to construct a multimodal corpus combining children’s verbal accounts, visual and cartographic artifacts, and self-generated analytical categories. Through a staged analytic process – curation, participatory synthesis, and consolidation – children collaboratively interpreted information, generated thematic categories, and prioritized feasible proposals for more child-friendly urban environments. Their analyses produced conceptually rich and actionable insights, emphasizing spatial concerns (mobility, accessibility, safety), relational-ecological dimensions (networks of care, intergenerational uses of space), and pragmatic solutions for local governance. Comparison with adult researchers’ interpretations revealed both areas of convergence and distinctive child-specific perspectives often overlooked in conventional analyses. The study presents a transferable, ethically grounded framework that enhances children’s interpretive agency, strengthens the authenticity of qualitative findings, and informs policies for inclusive and sustainable cities. Guidance is provided for researchers and institutions seeking to legitimize and integrate children’s analytical contributions within participatory knowledge generation.

MotivationMultiomics data analysis is essential for scientific discovery in precision medicine. However, translating analysis results of omics data analysis into novel scientific hypotheses remains a significant challenge. Human experts must manually review analysis results and generate new hypotheses based on extensive and interconnected biomedical prior knowledge, which is subjective and not scalable. While large language models can accelerate the discovery, their reasoning improves when grounded in structured, auditable, and comprehensive biomedical prior knowledge. However, biomedical knowledge is scattered across heterogeneous databases that use diverse and inconsistent nomenclature systems, making it difficult to integrate resources into a unified format for scalable analysis. This fragmentation limits the ability of artificial intelligence systems to fully leverage biomedical data for scientific discovery.ResultsWe developed BioMedGraphica, a novel all-in-one platform that harmonizes fragmented biomedical resources by integrating 11 entity types and 30 relation types from 43 databases into a unified textual prior knowledge graph containing 2 306 921 entities and 27 232 091 relations. In addition, we present a novel textual-numeric graph (TNG) data structure concept, where textual information captures prior biological knowledge (e.g. transcription start sites, functions, mechanisms), numeric values represent quantitative biomedical features, and the integrated relations can help uncover mechanisms. By bridging prior knowledge with user-specific data, TNG is a novel and ideal data structure for developing novel graph analysis models.Availability and implementationThe code is available at: https://github.com/FuhaiLiAiLab/BioMedGraphica and BioMedGraphica knowledge graph database can be downloaded from huggingface dataset: https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica

ObjectiveHealthcare systems struggle to balance the need for frontline problem-solving with the requirement for theory-driven strategies that ensure sustainable system-wide improvement. Implementation science, improvement science and quality improvement have emerged as complementary approaches to bridge gaps between evidence and practice, yet their integration remains limited. This scoping review examines how these disciplines intersect and can be applied to enhance HIV care delivery.MethodsWe conducted a scoping review of peer-reviewed articles published between 2016 and 2025. From an initial identification of 244 articles, 18 core studies were selected for snowball sampling, resulting in a pool of 113. After screening for accessibility and relevance, 30 studies were included in the final review that explicitly addressed overlaps between implementation science, improvement science and quality improvement. Data were charted on study objectives, methodologies, frameworks and relevance to healthcare improvement, and synthesised to identify common themes, models and barriers to integration.ResultsThe integration of these three disciplines creates a robust framework for health system change: implementation science emphasises fidelity and evidence-based uptake, improvement science prioritises generalisable knowledge and quality improvement enables rapid, local problem-solving. Their combined application can enhance the scalability, sustainability and efficiency of interventions. Models such as the HIV/AIDS Bureau Implementation Science Model, Reach-Effectiveness-Adoption-Implementation-Maintenance and the Learning Evaluation framework illustrate practical integration, showing how iterative quality improvement efforts can inform broader implementation strategies. Barriers include siloed approaches, variable terminology and limited organisational capacity, highlighting the need for cross-disciplinary collaboration, training and infrastructure support.ConclusionIntegrating implementation science, improvement science and quality improvement provides a pathway to accelerate evidence translation, strengthen system-wide healthcare quality and improve patient-centred outcomes in HIV care. Synthesising shared principles and alignment opportunities offers actionable guidance for healthcare systems seeking to leverage the strengths of each discipline for more effective, scalable and sustainable care delivery.

An Afrofuture of Global Health.

Using Diffusion of Innovations Theory, we investigated whether countries with higher innovation capacity showed earlier tipping points (shift from increasing to decreasing drunkenness) and steeper declines in adolescent drunkenness (2002-2022). Innovation capacity likely facilitates these shifts through knowledge generation, policy implementation, and norm diffusion. Trends in adolescent drunkenness were examined across 46 countries using six cross-sectional school-based survey waves from the international HBSC study (N = 319,843 15-year-olds). Data were complemented by country-level innovation capacity, per capita GDP, and Gini-coefficients. Two-level random effects models tested cross-level interactions between innovation capacity and linear and quadratic time trends in adolescent drunkenness frequency. Significant small-to-moderate cross-level interactions were found. Countries with high innovation capacity showed immediate linear declines (B = -.217, SE = .083), that flattened or showed an upward shift by 2022 (B = .031, SE = .007). Countries with low innovation capacity displayed an inverted U-shape trend in the early 2000s with a later tipping point (B = -.006, SE = .002). A steeper linear decline was observed for countries with higher (vs. lower) innovation capacity from their respective tipping point onward (B = -.273, SE = .083). Innovation capacity may accelerate adoption and diffusion of healthier behaviors through more rapid translation of health evidence into effective policy, parenting, and norms. While countries with high innovation capacity showed earlier declines, their initially higher levels of drunkenness may have created greater urgency for action. Earlier peaks and subsequent faster reductions in future alcohol-related health care needs are expected in these countries, though the possible recent trend reversal warrants close monitoring.

Green hydrogen in the Netherlands: A systemic assessment of status and barriers

Development of the INDIGO partnership knowledge exchange strategy

Metaphors we learn to sign by: Positive transfer effects of existing sign language expertise and gestural repertoire on metaphor inferencing in a novel sign language.

Combining memories of related experiences is fundamental to the formation of generalizable knowledge. Past work has shown that the ability to integrate and reason about related events improves across childhood. However, little work has examined developmental changes in the ability to actively construct new relational knowledge by making decisions about how to study related materials. We used a transitive inference (TI) task to examine the active construction of relational knowledge in 7- to 17-year-old children (N = 107). We find that age-related improvements in relational inference are accompanied by an increasing preference for "chained" study, such that overlapping relations are studied in consecutive trials. Using computational models of transitive inference, we show that these developmental changes are consistent with a growing tendency to link individual relations together into a single mental structure while learning. This process is facilitated when children study premises in chained sequences. These findings suggest that exploratory study behaviors that promote relational reasoning emerge late in childhood, developing alongside the capacity to maintain and manipulate more complex mental representations. (PsycInfo Database Record (c) 2026 APA, all rights reserved).