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Background: There has been a rapid increase in the number of, and demand for, organisations offering behavioural science advice to government over the last ten years. Yet we know little of the state of science and the experiences of these evidence providers. Aims and objectives: To identify current practice in this emerging field and the factors that impact on the production of high-quality and policy-relevant research. Methods: A qualitative study using one-to-one interviews with representatives from a purposeful sample of 15 units in the vanguard of international behavioural science research in policy. The data were analysed thematically. Findings: Relationships with policymakers were important in the inception of units, research conduct, implementation and dissemination of findings. Knowledge exchange facilitated a shared understanding of policy issues/context, and of behavioural science. Sufficient funding was crucial to maintain critical capacity in the units' workforces, build a research portfolio beneficial to policymakers and the units, and to ensure full and transparent dissemination. Discussion and conclusion: Findings highlight the positive impact of strong evidence-provider/user relationships and the importance of governments' commitment to co-produced research programmes to address policy problems and transparency in the dissemination of methods and findings. From the findings we have created a framework, 'STEPS' (Sharing, Transparency, Engagement, Partnership, Strong relationships), of five recommendations for units working with policymakers. These findings will be of value to all researchers conducting research on behalf of government.

In this Symposium we link different perspectives and traditions of research on language and concepts in the cognitive sciences to better understand the process of abstraction from the social-interactive standpoint. In contrast to the usual benefits of abstraction – such as the ability to categorize and generalize – we underscore the possibility of abstract concepts and words to remain underspecified, “open to the context, the suggestions of others” (Borghi, 2023) or to processes of real-time negotiations (Christiansen & Chater, 2022). This is enabled by their largely non-perceptual rela-tional character (Gentner, 2005) and by the fact that they arise in cognitive systems continually embedded and active in their environments (Cisek 1999; Mannella & Tummolini 2023).

There has been considerable interest exploring how the utility of an outcome impacts the probability with which it is mentally simulated. Earlier studies using varying methodologies have yielded divergent conclusions with different directions of the influence. To directly examine such mental process, we employed a random generation paradigm in which all the outcomes were either equally (i.e., followed a uniform distribution) or unequally (i.e., a binomial distribution) probable. While our results revealed individual differences in how the utility influenced responses, the overall findings suggested that it is the outcomes' probabilities, not their utilities, that guide this process. Notably, an initial utility-independent bias emerged, with individuals displaying a tendency to start with smaller values when all outcomes are equally likely. Our findings offer insights into the benefits of studying the mental sampling processes and provide empirical support for particular sampling models in this domain.

People solve a myriad of coordination problems without explicit communication every day. A recent theoretical account, virtual bargaining, proposes that, to coordinate, we often simulate a negotiation process, and act according to what we would be most likely to agree to do if we were to bargain. But very often several equivalent tacit agreements — or virtual bargains — are available, which poses the challenge of figuring out which one to follow. Here we take inspiration from virtual bargaining to develop a cognitive modeling framework for dynamic coordination problems. We assume that players recognize their common goal, identify one or more possible tacit agreements based on situational features, observe the history of their partner's choices to infer the most likely tacit agreement, and play their role in the joint plan. We test this approach in two experiments (n = 125 and n = 133) based on a dynamic coordination game designed to elicit agreement-based behavior. We fit our model at the individual level and compare its performance against alternative models. Across four different conditions, our model performs best among the set of models considered. Behavioral results are also consistent with players sustaining coordination and cooperation in the task by converging on tacitly agreed strategies or “virtual bargains”.

Recent decision making theories have explained behaviour using mental sampling mechanisms where people imagine possible outcomes to guide their choices. Simultaneously, work in other domains has found evidence of particular mental sampling patterns, such as autocorrelations between samples and moderation by prior assumptions, which current decision making theories do not generally consider. Here, we seek to unify this work, developing a new sampling model of preferential choice incorporating these findings in other domains. Our model, based on the Autocorrelated Bayesian Sampler, predicts choice, reaction time, confidence and valuation from a common underlying process. We find a strong correspondence between our model's predictions and empirical choice data, though performance remains below leading explanations for such tasks. Our model does however cover a broader set of response types than existing theories, suggesting the advantages of considering of a wider range of behaviours than are commonly examined in current decision making studies.

People's mental representations of complex stimuli, such as images of facial affect, are difficult to elicit. To address this challenge, methods such as Markov Chain Monte Carlo with People (MCMCP), integrate human agents into computer-based sampling algorithms. However, such methods suffer from slow convergence, making them impractical for recovering the representations of individuals. Here, we extended MCMCP by introducing an adapted Variational Auto-Encoder (VAE) with domain knowledge as an auxiliary agent, guiding the sampling process away from less useful experimental trials. To test this approach, we ran a new experiment comparing such a VAE-guided MCMCP against baseline MCMCP in terms of convergence speed and quality of recovering human representations of facial affect. Preliminary results demonstrated that most guided chains converged on an individual's facial affect representation within a single experimental session, faster than the baseline methods, and results showed the extent of individual differences in facial affect representations. Thus, VAE-guided MCMCP provides a promising framework for interfacing machine intelligence with psychological experiments to enhance our understanding of human cognition.

Individuals make biased and variable probability judgements. Recent models such as the Bayesian Sampler (Zhu, et al., 2020), Probability Theory Plus Noise (Costello & Watts, 2014), and the Quantum Sequential Sampler (Huang et al., 2023) capture a wide range of effects by assuming people are biased towards indifference (i.e., 0.5). However, in some experiments participants instead showed asymmetric bias, defined as a pull toward non-0.5 values. We investigated asymmetric bias in 5 experiments, where participants judged the probabilities of dice rolls. While participants' judgements were independent of whether they were in a high or low probability environment or the number of alternative options displayed, participants showed a bias toward low (

Random generation studies have shown that people struggle to be unpredictable – they slowly and effortfully produce autocorrelated sequences instead. However, true random processes (such as radioactive decay) are also not instantaneous. In this project we explore how long it takes people in a random generation task to be random. We do so in two experiments asking people to draw samples from naturalistic domains (lifespans and heights), manipulating either the rate of generation or the requirement to be random (within participants). Irrespective of pace or instructions, we find that people can produce a random sample every four to five seconds. Additionally, the time a person needs to produce random samples is consistent across conditions, but varies widely between people. Following previous literature, we model random generation performance as an autocorrelated sampling algorithm, giving a process level account of how people do these tasks and why they need time to be random.

Societal expectations have been found to determine which social roles (e.g., jobs) people should occupy. Previously, however, these beliefs have been mainly explored using implicit measures such as sequential priming tasks where responding to expected (vs. conflicting) information is facilitated. We applied a random generation paradigm where participants said aloud the first names of hypothetical people working in various professions. This revealed that more female (male) first names were uttered for the female-typical (male-typical) occupations reflecting the societal gender stereotypes and the environmental statistics. Furthermore, the proportion of female and male names generated for each profession predicted participants' performance in a sequential priming task (prime = professions from random generation task, target = female vs. male face) better than the environmental statistics or participants' explicit gender ratio estimates of these jobs. Collectively, these findings offer a new method for exploring the internal representations elicited by cultural expectations.

Purpose: Physical education (PE) teachers' interactions with students were explored to examine self-selection for PE teaching as a career option during school. Method: Semistructured life story interviews were conducted with 29 PE teachers at different career stages. Complementing occupational socialization, Bourdieu's habitus, capital, field, and practice were adopted as thinking tools to inform thematic analysis. Results: Three key themes were identified: (a) acceptance into the inner sanctum based on physical competence, effort, and enthusiasm for the traditional curriculum; (b) opportunities provided to students accepted into the inner sanctum, and (c) outside the inner sanctum: mismatched habitus and self-selection for PE teaching. Conclusion: Students exchanged competence, effort, and enthusiasm in the traditional curriculum for acceptance and opportunities to encourage self-selection for teaching PE. Without acceptance, individuals experienced challenges gaining career support. Dominated by a homogenous group resistant to change, PE needs independent careers information to promote change through heterogeneity.

Abstract Neurons receive thousands of inputs onto their dendritic arbour, where individual synapses undergo activity-dependent plasticity. Long-lasting changes in postsynaptic strengths correlate with changes in spine head volume. The magnitude and direction of such structural plasticity - potentiation (sLTP) and depression (sLTD) - depend upon the number and spatial distribution of stimulated synapses. However, how neurons allocate resources to implement synaptic strength changes across space and time amongst neighbouring synapses remains unclear. Here we combined experimental and modelling approaches to explore the elementary processes underlying multi-spine plasticity. We used glutamate uncaging to induce sLTP at varying number of synapses sharing the same dendritic branch, and we built a model incorporating a dual role Ca2+-dependent component that induces spine growth or shrinkage. Our results suggest that competition among spines for molecular resources is a key driver of multi-spine plasticity and that spatial distance between simultaneously stimulated spines impacts the resulting spine dynamics.

Abstract Background Most rural populations experience significant health disadvantage. Community-engaged research can facilitate research activities towards addressing health issues of priority to local communities. Connecting scholars with community based frontline practices that are addressing local health and medical needs helps establish a robust pipeline for research that can inform gaps in health provision. Rural Health Projects (RHPs) are conducted as part of the Doctor of Medicine program at the University of Queensland. This study aims to describe the geographic coverage of RHPs, the health topic areas covered and the different types of RHP research activities conducted. It also provides meaningful insight of the health priorities for local rural communities in Queensland, Australia. Methods This study conducted a retrospective review of RHPs conducted between 2011 and 2021 in rural and remote Australian communities. Descriptive analyses were used to describe RHP locations by their geographical classification and disease/research categorisation using the International Classification of Diseases and Related Health Problems – 10th Revision (ICD-10) codes and the Human Research Classification System (HRCS) categories. Results There were a total of 2806 eligible RHPs conducted between 2011 and 2021, predominantly in Queensland (n = 2728, 97·2%). These were mostly conducted in small rural towns (under 5,000 population, n = 1044, 37·2%) or other rural towns up to 15,000 population (n = 842, 30·0%). Projects mostly addressed individual care needs (n = 1233, 43·9%) according to HRCS categories, or were related to factors influencing health status and contact with health services (n = 1012, 36·1%) according to ICD-10 classification. Conclusions Conducting community focused RHPs demonstrates a valuable method to address community-specific rural health priorities by engaging medical students in research projects while simultaneously enhancing their research skills.

This study delves into the influence of varying solvent compositions on the extraction of Total Phenolic Compounds (TPC) and the antioxidant activities of extracts from Mentha suaveolens subsp. timija leaves and stems. The extraction process is conducted using ultrasound-assisted extraction via an ultrasonic bath. Employing a surface mixture design approach, we explored the singular use of Water (W), Methanol (M), and Ethanol (E), as well as their combinations. The outcomes demonstrate that solvents' compositions significantly influence the extraction of Total Phenolic Content (TPC), with noteworthy synergistic effects observed in specific combinations, such as a ratio of W:M (1/2:1/2). The scavenging activity of DPPH and the Total Antioxidant Capacity (TAC) were also evaluated, indicating that certain combinations of solvents, particularly those involving Methanol and water, enhance the antioxidant activities. The results reveal that solvent compositions significantly influence TPC extraction, with notable synergistic effects observed in specific mixtures, such as W:M (1/2:1/2). The Pareto chart analysis highlights the substantial contributions of Methanol, Ethanol, and Water to TPC recovery and antioxidant activities. The findings underscore the importance of solvent optimization for extracting bioactive compounds, providing valuable insights for researchers and industries seeking to harness the full potential of this species in various applications.

Abstract Background Reducing and breaking up sitting is recommended for optimal management of Type 2 diabetes mellitus (T2DM). Yet, there is limited evidence of interventions targeting these outcomes in individuals with this condition. The primary aim of this study was to assess the feasibility and acceptability of delivering and evaluating a tailored online intervention to reduce and break up sitting in adults with T2DM. Methods A mixed-methods two-arm randomised controlled feasibility trial was conducted in ambulatory adults with T2DM who were randomised 1:1 to the REgulate your SItting Time (RESIT) intervention or usual care control group. The intervention included online education, self-monitoring and prompt tools (wearable devices, smartphone apps, computer apps) and health coaching. Feasibility outcomes were recruitment, attrition, data completion rates and intervention acceptability. Measurements of device-assessed sitting (intended primary outcome for definitive trial), standing and stepping, and physical function, psychosocial health and wellbeing were taken at baseline, 3 months and 6 months. Individual semi-structured interviews were conducted at six-months (post intervention) to explore acceptability, feasibility and experiences of the trial and intervention using the Framework Method. Results Seventy participants aged 55 ± 11 years were recruited. Recruitment rate (proportion of eligible participants enrolled into the study) was 67% and participant retention rate at 6 months was 93% (n = 5 withdrawals). Data completion rates for daily sitting were 100% at baseline and ranged from 83 to 91% at 3 months and 6 months. Descriptive analysis demonstrated potential for the intervention to reduce device-measured sitting, which was 30.9 ± 87.2 and 22.2 ± 82.5 min/day lower in the intervention group at 3 and 6 months, respectively, compared with baseline. In the control group, sitting was 4.4 ± 99.5 and 23.7 ± 85.2 min/day lower at 3 and 6 months, respectively. Qualitative analysis identified three themes: reasons for participating in the trial, acceptability of study procedures, and the delivery and experience of taking part in the RESIT intervention. Overall, the measurement visits and intervention were acceptable to participants. Conclusions This study demonstrated the feasibility and acceptability of the RESIT intervention and evaluation methods, supporting a future definitive trial. If RESIT is found to be clinically effective, this could lead to changes in diabetes healthcare with a focus on reducing sitting. Trial registration The trial was registered with ISRCTN (number ISRCTN14832389).

Recent work suggests that people produce random sequences by tapping into a general ability to derive probabilistic inferences through sampling an internal belief distribution. In contrast, previous work has proposed that participants monitor the production of inherently deterministic sequences, changing strategy when randomness appears low. Experiments exploring this process have highlighted the role of task requirements (e.g., production pace, cognitive load), finding that randomness decreased when demands increased.However, assuming random generation stems from sampling for inference, increasing production rates might affect sequential dependencies and the overall sample distribution independently. For example, increased production rates might result in more predictable sequences but leave the overall distribution of the sample intact. Here, we assessed the effects of production rates on sequential statistics and overall distributional properties in a preregistered experiment in which participants produced people's lifespans. We discuss our results in terms of computational models of sampling for inference.

Effectively updating one’s beliefs requires sufficient empirical evidence (i.e., data) and the computational capacity to process it. Yet both data and computational resources are limited for human minds. Here, we study the problem of belief updating under limited data and limited computation. Using information theory to characterize constraints on computation, we find that the solution to the resulting optimization problem links the data and computational limitations together: when computational resources are tight, agents may not be able to integrate new empirical evidence. The resource-rational belief updating rule we identify offers a novel interpretation of conservative Bayesian updating.

Contractualist moral theories hold that morality is primarily about acting according to what would be agreed by rational agents. The contractualist tradition has received little attention in empirical work compared to competing normative ethical theories that are primarily concerned with rules (deontology) and consequences (consequentialism). Recent theoretical developments and empirical results suggest that agreement-based considerations and forms of reasoning could play a central role in moral judgment and decision making. However, the computational foundations of moral contractualism have scarcely been explored. In this paper, we present a flexible experimental paradigm to study contractualist moral behavior in an incentivized setting. We then develop a simple computational model of agreement-based moral decision making that captures participants’ behavior in the task. Results suggest that agreement-based cognitive processes are required to explain the nuances of observed behavioral patterns. Contractualism could offer a fruitful framework to understand how humans coordinate their behavior in morally ambiguous contexts.

It is now commonplace to hear that addressing the grand challenges of today’s society – climate change, obesity, ageing populations, pandemics – requires substantial changes in individuals’ behaviour (e.g., Newell & Moss, 2021). This call to arms places cognitive and behavioral science at the forefront of understanding how such widespread change can be achieved. Answering that call has led many researchers to make bold claims for the potential of simple techniques that facilitate positive behaviour change without impinging on people’s freedom of choice (e.g., Thaler & Sunstein, 2008). These techniques, collectively and colloquially known as ‘nudges’ capitalize on promoting ‘desirable’ options by making changes to the choice architectures (physical, social and psychological) in which decisions are made.

Social learning through friendships is important in child development. Autistic children often initiate and engage in social interactions differently than neurotypical peers. LEGO® based therapy is a group intervention which facilitates social interactions with peers using collaborative LEGO® play. A 1:1 cluster randomised controlled trial with autistic children aged 7-15 comparing 12 weeks' LEGO® based therapy and usual support to usual support alone in 98 mainstream schools (2017-2019) was carried out. The primary outcome was social skills (Social Skills Improvement System) completed by unblinded teachers (not intervention deliverers) at 20 weeks. Analysis used intention-to-treat. Fifty intervention schools (127 participants) and 48 control schools (123 participants) were allocated. Primary analysis included 45 intervention schools (116 participants) and 42 control schools (101 participants). The between-arms difference was 3.74 (p = 0.06, 95% confidence interval: -0.16, 7.63) and 1.68 (p = 0.43, 95% confidence interval: -2.51, 5.87) at 20 and 52 weeks (0.18 and 0.08 standardised effect sizes). Twenty-week outcomes for those receiving per protocol intervention were 4.23 (95% confidence interval 0.27, 8.19) with a standardised effect size of 0.21. Sensitivity estimates were between 3.10 and 4.37 (0.15-0.21 standardised effect sizes). Three unrelated serious adverse events were reported. LEGO® based therapy has a small positive non-significant benefit for social skills at 20 weeks but not 52 weeks.

This article provides experimental and numerical data pertaining to the compressive testing and model calibration for a novel design of 316 L stainless steel equal angle sections (EAS) produced through additive manufacturing, wherein each leg of the EAS is replaced by a wavy surface resembling high order buckling modes of the flat plate. The experimental data were acquired from testing 9 unique stub column sections, in all combinations of 3 different thicknesses and 2 wave magnitudes, with a control section provided for each thickness. The provided numerical data was produced to calibrate a finite element model of the tested sections by varying imperfection magnitudes, and selected values fit strongly to the physical tests. Both physical and numerical tests data herein are given in two parts each, one summary spreadsheet describing section geometry and peak load, and one more detailed spreadsheet providing load-displacement history for all physical sections and selected finite element sections. This data provides insight into finite element analysis of additively manufactured stainless steel sections, making it valuable for the validation of numerical models and stainless steel material behaviour.

Abstract Background Inequities of health outcomes persist in rural populations globally. This is strongly associated with there being less health coverage in rural and underserviced areas. Increasing health care coverage in rural area requires rural health system strengthening, which subsequently necessitates having tools to guide action. Objective This mapping review aimed to describe the range of tools, frameworks and resources (hereafter called tools) available globally for rural health system capacity building. Methods This study collected peer-reviewed materials published in 15-year period (2005–2020). A systematic mapping review process identified 149 articles for inclusion, related to 144 tools that had been developed, implemented, and/or evaluated (some tools reported over multiple articles) which were mapped against the World Health Organization’s (WHO’s) six health system building blocks (agreed as the elements that need to be addressed to strengthen health systems). Results The majority of tools were from high- and middle-income countries (n = 85, 59% and n = 43, 29%, respectively), and only 17 tools (12%) from low-income countries. Most tools related to the health service building block (n = 57, 39%), or workforce (n = 33, 23%). There were a few tools related to information and leadership and governance (n = 8, 5% each). Very few tools related to infrastructure (n = 3, 2%) and financing (n = 4, 3%). This mapping review also provided broad quality appraisal, showing that the majority of the tools had been evaluated or validated, or both (n = 106, 74%). Conclusion This mapping review provides evidence that there is a breadth of tools available for health system strengthening globally along with some gaps where no tools were identified for specific health system building blocks. Furthermore, most tools were developed and applied in HIC/MIC and it is important to consider factors that influence their utility in LMIC settings. It may be important to develop new tools related to infrastructure and financing. Tools that have been positively evaluated should be made available to all rural communities, to ensure comprehensive global action on rural health system strengthening.

Abstract Background Recent findings from studies of mouse models of Mendelian disorders of epigenetic machinery strongly support the potential for postnatal therapies to improve neurobehavioral and cognitive deficits. As several of these therapies move into human clinical trials, the search for biomarkers of treatment efficacy is a priority. A potential postnatal treatment of Kabuki syndrome type 1 (KS1), caused by pathogenic variants in KMT2D encoding a histone-lysine methyltransferase, has emerged using a mouse model of KS1 (Kmt2d +/βGeo ). In this mouse model, hippocampal memory deficits are ameliorated following treatment with the histone deacetylase inhibitor (HDACi), AR-42. Here, we investigate the effect of both Kmt2d +/βGeo genotype and AR-42 treatment on neuroanatomy and on DNA methylation (DNAm) in peripheral blood. While peripheral blood may not be considered a “primary tissue” with respect to understanding the pathophysiology of neurodevelopmental disorders, it has the potential to serve as an accessible biomarker of disease- and treatment-related changes in the brain. Methods Half of the KS1 and wildtype mice were treated with 14 days of AR-42. Following treatment, fixed brain samples were imaged using MRI to calculate regional volumes. Blood was assayed for genome-wide DNAm at over 285,000 CpG sites using the Illumina Infinium Mouse Methylation array. DNAm patterns and brain volumes were analyzed in the four groups of animals: wildtype untreated, wildtype AR-42 treated, KS1 untreated and KS1 AR-42 treated. Results We defined a DNAm signature in the blood of KS1 mice, that overlapped with the human KS1 DNAm signature. We also found a striking 10% decrease in total brain volume in untreated KS1 mice compared to untreated wildtype, which correlated with DNAm levels in a subset KS1 signature sites, suggesting that disease severity may be reflected in blood DNAm. Treatment with AR-42 ameliorated DNAm aberrations in KS1 mice at a small number of signature sites. Conclusions As this treatment impacts both neurological deficits and blood DNAm in mice, future KS clinical trials in humans could be used to assess blood DNAm as an early biomarker of therapeutic efficacy.

Coriander, caraway, and mystical cumin are famous for their aromatic properties and widely used in Moroccan cuisine. The nutritional/phytochemical composition of their seeds (used for food flavoring and preservation) were compared. Their antioxidant, anti-inflammatory, cytotoxic and hepatotoxic effects were also explored. The fat content was similar among the samples (13%), with monounsaturated fatty acids being predominant. The coriander and mystical cumin seeds were extremely rich in C18:1n9c (81 and 85%, respectively) while, in the caraway, C18:1n12 (25%) was found together with C18:1n9c (32%). The caraway seeds also presented a higher proportion of C18:2n6c (34%) than the other seeds (13 and 8%, correspondingly). γ-Tocotrienol was the major vitamin E form in all the samples. The caraway seeds contained double the amount of protein (~18%) compared to the other seeds (~8%) but, qualitatively, the amino acid profiles among all seeds were similar. The seeds were also rich in dietary fiber (40–53%); however, differences were found in their fiber profiles. Caraway showed the highest antioxidant profile and anti-inflammatory activity and an LC-DAD-ESI/MSn analysis revealed great differences in the phenolic profiles of the samples. Cytotoxicity (NCI-H460, AGS, MCF-7, and CaCo2) and hepatotoxicity (RAW 264.7) were not observed. In sum, besides their flavoring/preservation properties, these seeds are also relevant source of bioactive compounds with health-promoting activities.