Abstract. While there is extensive literature exploring the possible negative effects of video games, and many such studies using college student samples, there is little research on how video game...

Task decisions and confidence ratings are fundamental measures in metacognition research, but using these reports requires collecting them in some order. Only three orders exist and are used in an ad hoc manner across studies. Evidence suggests that when task decisions precede confidence, this report order can enhance metacognition. If verified, this effect pervades studies of metacognition and will lead the synthesis of this literature to invalid conclusions. In this Registered Report, we tested the effect of report order across popular domains of metacognition and probed two factors that may underlie why order effects have been observed in past studies: report time and motor preparation. We examined these effects in a perception experiment (n = 75) and memory experiment (n = 50), controlling task accuracy and learning. Our registered analyses found little effect of report order on metacognitive efficiency, even when timing and motor preparation were experimentally controlled. Our findings suggest the order of task decisions and confidence ratings has little effect on metacognition, and need not constrain secondary analysis or experimental design.

Displaying high effort at work is rewarded with more positive moral judgments (effort moralization effect) and increased cooperation partner attractiveness. This holds, even if higher effort is unrelated to better performance. Yet, current evidence is exclusively based on males, mostly situated in the work context. This prohibits generalization to the full population and neglects critical aspects of our lives, such as the care context (e.g., unpaid care for elders). To address this gap, we conducted two Studies (Study 1: Nwork = 859, Study 2: Ncare = 701) testing the effect between genders and contexts—work and care. Study materials featured two actors performing the same task, requiring different levels of effort (high/low). Participants rated the actor’s morality, suggested hourly salary, and reported their satisfaction to cooperate with them as assigned partners. The results confirmed the effort moralization effect in work contexts but were mixed for the care context, potentially due to the inherently moral nature of the behavior. There were no gender differences, supporting the demographic generalizability of the effect. Effort did not influence suggested pay, and participants expressed greater satisfaction with low-effort actors as assigned cooperation partners. While further research is needed to explore the boundary conditions of effort moralization in different contexts, the findings support its role as a robust heuristic for moral judgment in the work context.

Objective: The study's principal aim was to explore the usefulness of the Harmful Dysfunction Analysis (HDA) in identifying individuals with pathological social media use (PSMU) and potentially other behavioral addictions as an alternative to using DSM-5-TR-based diagnostic criteria for substance use disorders (SUD) or research criteria for internet gaming disorder (GD). Method: Using Swiss data (N = 7,510) from the Health Behaviour in School-aged Children Study 2018, we tested weaker (HDA1) and stronger (HDA2) HDA versions. We examined differences between HDA cases and non-cases, convergence between different scoring methods, and between groups differences distinct to each scoring method (i.e., non-overlapping cases) on measures of physical health (physical activity and body mass index) and mental health (psychosomatic health, life satisfaction, school well-being), with models adjusted for age, gender, migration status, and family affluence. Data from Hungary (N = 3,789) was selected to repeat the analysis as a sensitivity investigation. Results: SUD-based scoring yielded the highest PSMU prevalence of 33.2% while GD-based prevalence was 9%. HDA1 and HDA2 scorings yielded PSMU prevalence of 22.2% and 4.2%, respectively. HDA1-based PSMU cases showed poorer physical and mental health than non-cases with differences of small-to-medium effect size, whereas HDA2 differences were of large effect size. SUD-based cases that overlapped with HDA scoring showed worse physical and mental health than non-overlapping SUD-based cases. Non-overlapping GD and HDA cases showed no significant differences on validators that survived the sensitivity evaluation. Conclusions: HDA may reduce PSMU prevalence while preserving conceptual and clinical validity. The more demanding HDA2 approach exhibited more convincing validator results than HDA1. From the HDA perspective, substantial SUD-based cases were false positives whereas GD-based scoring produced both false positives and negatives. Our findings suggest that further examination of HDA for advancing the conceptualization of addictive disorders is warranted.

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Presented by OSF

One of the key areas in the scientific programs of addictive behaviors is the research on measurement. In the present study, we focus on the survey measurement of gaming disorder. In particular, we tested the gambling hypotheses: whether survey studies on gaming disorder are potentially contaminated by gambling behavior data and thus do not reflect actual gaming behaviors. A systematic review of survey materials among the most cited studies (N=500) provided confirmatory evidence for a systematic error in the literature. The majority of research in the field is contaminated by a measurement error stemming from conceptual confusion. This problem is linguistic and does not concern all languages to the same degree. Additionally, we surveyed English (n=312) and Slovak (n=319) people to explore further reasons for the error. Exploration revealed various terminological confusions in both languages. For instance, half of the participants (EN=48.7%/SK=59.1%) interpreted “gambling” to also refer to “gaming”, including offline gambling like poker (EN=68.6%/SK=62.5%). Meanwhile, the majority interpreted offline activities like board games (EN=50.3%/SK=62%) to be gaming too. The findings suggest that the systematic measurement error is unlikely to be easily correctable through self-report instructions, as people interpret gaming and gambling in many inconsistent ways. We recommend gaming disorder research to seek alternatives to survey data.

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Editors' Summary: This Replication Study has reproduced some parts of the original paper but it also contains results that are not consistent with other parts of the original paper.

Background: Providing informal care to persons with dementia (PWD) living at home can be challenging and lead to experience of caregiver stress and depression. Interventions delivered through mobile applications (apps) provide innovative solutions for community-based social care professionals to address the increasing support needs of family caregivers (FCs) to PWD. Objective: This study aimed to examine, among FCs to PWD living at home, a) the potential association between professional support provided through a mobile app and caregiver stress and depressive symptoms; b) types of support provided through chat interaction between FCs and social care professionals; c) how provision of support provided through a mobile app relates to changes in caregiver stress and depressive symptoms. Methods: A mixed-methods pilot study was conducted integrating quantitative pre- and post-intervention data and qualitative logged chat data. FCs to PWD living at home (n=35) were recruited to test a tailor-made mobile app over eight weeks. The outcome measures were caregiver stress (primary) and depressive symptoms (secondary). Descriptive statistics were used to describe socio-demographic factors. Inferential statistics were used to analyse mean differences in the outcome measures pre- and post-intervention. FCs were divided into three groups based on changes in caregiver stress scores between pre- and post-intervention. Generalized linear models (GLM) analyses were used to determine the association between participation in the intervention on caregiver stress and depressive symptoms, controlling for age, gender and relationship to the PWD. Logged chat data was analysed using summative content analysis to identify types of support provided and received. Changes in caregiver stress were integrated with the chat data to determine patterns in the types of support received. Results: The mean age of the FCs was (69.4), with most being women (80%), partners (68.6%) and living together with the PWD (74%). The mean score of FCs' caregiver stress was marginally higher post-intervention (24.1, SD 9.3) compared to pre-intervention (23.9, SD 9.2), while the mean score of their depressive symptoms declined between pre- (6.5, SD 5.1) and post-intervention (6.2, SD 5.2). These differences were not statistically significant. Regression analyses showed that participation in the intervention was not statistically significantly associated with caregiver stress (β=0.171, α=.05, P=.862) or depressive symptoms (β= -0.293, α=.05, P=.745) after adjusting for age, gender and relationship to the PWD. However, mixed-methods analysis at the sub-group level, suggests that frequently provided tailored support by social care professionals delivered through a mobile app potentially can reduce caregiver stress among FCs to PWD living at home. Conclusions: The study highlights the importance of providing frequent and tailor-made support to meet the individual needs of FCs to PWD. The findings from this study can help community-based social care providers plan and organize the content of digital support provided for FCs to PWD living at home.

Schnall, Benton, and Harvey (2008) hypothesized that physical cleanliness reduces the severity of moral judgments. In support of this idea, they found that individuals make less severe judgments wh...

Background: Concerns have been expressed about the abundance of new clinical prediction models (CPMs) proposed in the literature. The extent of this proliferation in prediction research, however, remains unclear. Objective: To estimate the total and annual number of CPM development publications available for all medical fields. Methods: Using a validated search strategy, we conducted a systematic search for prediction model studies published in Pubmed and Embase between 1995 and the end of 2020. By taking random samples for each year, we identified eligible studies that developed a multivariable model (diagnostic or prognostic) for individual-level prediction of a health outcome across all medical fields. Exclusion criteria included the development of models with a single predictor, studies not concerning humans, methodological studies, conference abstracts, articles with unavailable full text, and studies not available in English. Next, we estimated the total and annual number of published regression-based multivariable CPM development articles, based on the total number of publications, proportion of included articles and search sensitivity. Furthermore, we used an adjusted Poisson regression to extrapolate our results to years 1950-2024. Additionally, we estimated the number of articles developing non-regression-based CPMs. Results: From a random sample of 10,660 articles published between 1995 and 2020, 109 regression-based CPM development articles were included. We estimated that 82,772 (95%CI: 65,313-100,231) CPM development articles using regression were published, with an acceleration in model development from 2010 onward. With the addition of articles that used other techniques than regression (e.g., machine learning), the number rose to 147,714 (125,201-170,226). After extrapolation to 1950-2024, numbers increased to 156,673 and 248,431 for regression-based models and all models, respectively. Conclusions: Based on a representative sample of publications from the literature, we estimate that close to 250,000 articles reporting the development of clinical prediction models for all medical fields have been published until 2024. CPM development publication is ever increasing. To prevent research waste and to close the gap between research and clinical practice, focus should shift away from developing new CPMs to facilitating model validation and impact assessment of the plethora of available CPMs. Limitations of this study include restriction of search to articles available in English and development of the validated search strategy prior to the popularity of artificial intelligence and machine learning models.

Background: Falls are a prevalent and serious health condition among older people in residential aged care facilities, causing significant health and economic burdens. However, the likelihood of future falls can be predicted, and thus, falls can be prevented if appropriate prevention programs are implemented. Current fall prevention programs in residential aged care facilities rely on risk screening tools with suboptimal predictive performance, leading to significant concerns regarding resident safety. Objective: This study aimed to develop a predictive, dynamic dashboard to identify residents at risk of falls with associated decision support. This paper provides an overview of the technical process, including the challenges faced and the strategies used to overcome them during the development of the dashboard. Methods: A predictive dashboard was co-designed with a major residential aged care partner in New South Wales, Australia. Data from resident profiles, daily medications, fall incidents, and fall risk assessments were used. A dynamic fall risk prediction model and personalized rule-based fall prevention recommendations were embedded in the dashboard. The data ingestion process into the dashboard was designed to mitigate the impact of underlying data system changes. This approach aims to ensure resilience against alterations in the data systems. Results: The dashboard was developed using Microsoft Power BI and advanced R programming by linking data silos. It includes dashboard views for those managing facilities and for those caring for residents. Data drill-through functionality was used to navigate through different dashboard views. Resident-level change in daily risk of falling and risk factors and timely evidence-based recommendations were output to prevent falls and enhance prescriptive decision support. Conclusions: This study emphasizes the significance of a sustainable dashboard architecture and how to overcome the challenges faced when developing a dashboard amid underlying data system changes. The development process used an iterative dashboard co-design process, ensuring the successful implementation of knowledge into practice. Future research will focus on the implementation and evaluation of the dashboard’s impact on health processes and economic outcomes.

There are a myriad of obstacles faced by individuals who take medication for opioid use disorder, including high out-of-pocket costs, stigma, logistical challenges associated with traveling to treatment facilities, and negative experiences with treatment providers. The proliferation of illicit fentanyl use and associated overdose risk underscores the urgent need to broaden access to lifesaving pharmacotherapy for opioid use disorder. This case report describes the safe and effective induction of a 32-year-old male onto sublingual buprenorphine in a digital care setting, with integrated, counselor-facilitated psychosocial treatment delivered via a smartphone app targeting relapse prevention. The digital care modality enabled this patient to overcome 2 major treatment barriers: limited access to evidence-based treatment given his residence in a rural area, and heightened overdose risk given his use of fentanyl, a potent synthetic opioid. In addition, we describe tobacco cessation treatment delivered digitally concurrently with opioid use disorder care, combining pharmacotherapy and behavioral skills training. Given the disproportionately high rate of co-occurring opioid use disorder and tobacco use and associated mortality rates, the effective treatment of these conditions simultaneously in this case advances our knowledge of potentially efficacious treatment approaches for underserved individuals with opioid use disorder who present with polysubstance use.

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Mindfulness meditation has been suggested to protect mental health and enhance cognitive functions. However, the effectiveness of mindfulness breathing meditation for the general population in Malaysia has not been well documented. This study investigated the effects of mindfulness breathing meditation on perceived stress levels and cognitive functions (i.e., visual attention, inhibitory control, and cognitive flexibility) using heart rate variability (HRV) and eye-tracking methods. Fifty Malaysian adults aged between 18 and 34 years participated in this study. Participants were randomly allocated to either mindfulness breathing meditation or active control (music therapy) groups. Participants underwent a four-week intervention consisting of 30 min of online classes once a week and 10 min of daily meditation self-practice or music listening. The results showed significant improvement in cognitive flexibility and reduction in perceived stress levels after the intervention in the mindfulness breathing meditation group compared to the active control group. Participants in the mindfulness breathing meditation group self-reported this intervention as highly acceptable and effective in promoting stress reduction, emotional regulation, and attentional control. However, no significant improvement was found in attention, inhibitory control, and HRV after the intervention, suggesting that the mindfulness breathing meditation had no effect on these variables. While short-term engagement with mindfulness breathing meditation practice is achievable, the three-month follow-up using the Mindfulness Adherence Questionnaire showed that sustaining long-term adherence remains a challenge.

Background: COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. Objective: This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. Methods: We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. Results: Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India’s speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. Conclusions: Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.

Background: Mobile Health (mHealth) interventions offer a promising way to support healthy lifestyle habits, but effectiveness depends on user engagement. Maintaining high user engagement in app-based interventions is important, yet challenging. Objective: We aimed to examine the association between user engagement with an app-based dietary education for people with type 2 diabetes and changes in diet quality, dietary intake, and clinical measures. Methods: In this randomized clinical trial, people with type 2 diabetes were recruited within primary care and randomized 1:1 to a 12-week smartphone-delivered app-based dietary education or control group. Participants were followed up after 3-, 6- and 12-months. Dietary intake was assessed using a food frequency questionnaire. The control group received the app at the 3-month follow-up. User engagement was analysed among all participants. Categories of high (100%), moderate (50-99.9%), and low (<50%) user engagement were created based on the percentage of activities completed in the app. We used paired t-tests to compare mean changes in diet quality, dietary intake and clinical markers within user engagement groups, and fitted linear regression models to analyse differences in change between groups. Results: Data from 119 participants (60.5% men) was analysed. Mean age at baseline was 63.2 years and mean BMI was 30.1 kg/m2. User engagement was high with an average of 77.1% of app activities completed. More than half (53.8%) of users showed high user engagement, 21.8% moderate, and 24.4% low. Directly following the app-based education, a significant difference in change was seen for whole grains (β=20.4, 95%CI: 0.57-40.3) in participants with high user engagement compared to the low user engagement group who decreased their intake (p=0.03). At follow-up after 6 to 9 months after completed education, significant differences in change were seen for fibre, wholegrains, carbohydrates, saturated fat, sodium, and total energy in the moderate compared to the low engagement group, and a significant difference in change was seen for carbohydrates in the high, compared to the low, user engagement group. Conclusions: User engagement was generally high for the smartphone-based dietary education, suggesting that an app targeting dietary habits is feasible to use. Those with higher user engagement seem to maintain healthier dietary behaviours over time, compared to those with low user engagement. Future mHealth interventions should focus on ways to engage those with low interest. Clinical Trial: ClinicalTrials.gov NCT03784612; https://www.clinicaltrials.gov/study/NCT03784612

Background: Digital health interventions can support health-related knowledge transfer, for example through websites or mobile applications, and may reduce health inequalities by making health care available, where access is difficult, and by translating content to overcome language barriers. However, digital health intervention can also increase health inequalities due to the digital divide. To reach digitally excluded populations, design and delivery mechanisms need to specifically address this issue.

The present study replicated and extended prior research by comparing the effects of reviewing notes in groups vs. reviewing notes individually on individual final test performance. We also examined the potential interaction between reviewing delay and reviewing methods. Finally, students completed a questionnaire, the results of which reveal how students perceive the effectiveness of group vs. individual reviewing methods. In this experiment, students watched and took notes on two lectures. Following a short or long delay, students reviewed their notes either individually or in a group and were allowed to update their notes during these sessions. After the reviewing phase, students completed a final test for each lecture. We found that individuals added more idea units to their notes after reviewing notes in a group, and this beneficial effect was greater after a longer delay compared to a shorter delay. However, more new idea units did not translate into better cued recall performance. Our findings suggest that reviewing notes in a group helps individuals add more overlooked idea units in their notes, but more factors should be considered when studying the relationship between reviewing notes in a group and final test performance.

According to the action-specific account of perception, perception is scaled by one’s ability to act in interaction with environmental objects. Witt et al. (2005) were the first to report the tool-use effect that supports this notion. In their study, participants either used a reach-extending tool to touch the targets or reached out to the targets with their finger. Their results indicated that targets appeared closer when participants reached with the tool. The present study aims to directly replicate their study as a registered report to confirm the previous findings. Additionally, we will further investigate whether the inherent functionality of a tool influences perceived distance. To explore this, the tool’s inherent functionality will be manipulated while maintaining the tool’s physical length unchanged. In the same reaching task, we predict that alterations in a tool’s functionality are likely to influence perceived distance, even if the tool’s physical length remains constant.

When retrieving information, people often shift over time from “Remembering” high levels of detail about a study episode to simply “Knowing” the information absent such detail. This “Remember-Know” shift is well-documented for true information, and recent work suggests that this effect exists, but is attenuated, for false information. One explanation for this difference is that true information is better represented in people’s prior knowledge, supporting retention of this content as “Known” over time. In this registered report we tested this hypothesis by measuring people’s reported retrieval experiences (e.g., “Remembering” or “Knowing”) for true and false information at two levels of anticipated prior knowledge. While we replicate the “Remember-Know” shift, we do not find that it differs by anticipated prior knowledge. We also examine the relation between retrieval experiences and the production of encountered information, as well as the impact of repeated testing on retrieval experiences.

The question of whether and, if so, how creativity and unethical behavior such as dishonesty are related to each other has been addressed in multiple studies, with mixed results overall. The aim of this Registered Report is to shed further light on this issue. We first present a meta-analysis on the relation between creativity and dishonesty comprising the samples from a pre-registered multi-lab study (on a different topic), which indicated no relation between the constructs in question (k = 19, N = 2,154, rp = .02). Next, we examined the relation between creativity and dishonesty in a study (N = 1,152), in which we addressed several limitations of previous research. Specifically, we examined relations between comprehensively assessed creativity and dishonesty using subjective and objective indicators for both constructs. We found mixed results concerning the relation between creativity and dishonesty. In the majority of the confirmatory statistical tests, subjective creativity was positively related, whereas objective creativity was negatively related to dishonesty in the mind game. However, in exploratory analyses, we found that neither subjective nor objective creativity was related to dishonesty in the second dishonesty measure, the sender–receiver game.

A critical step before data-sharing of human neuroimaging is removing facial features to protect individuals’ privacy. However, not only does this process redact identifiable information about individuals, but it also removes non-identifiable information. This introduces undesired variability into downstream analysis and interpretation. This registered report investigated the degree to which the so-called defacing altered the quality assessment of T1-weighted images of the human brain from the openly available “IXI dataset”. The effect of defacing on manual quality assessment was investigated on a single-site subset of the dataset (N = 185). By comparing two linear mixed-effects models, we determined that four trained human raters’ perception of quality was significantly influenced by defacing by modeling their ratings on the same set of images in two conditions: “nondefaced” (i.e., preserving facial features) and “defaced”. In addition, we investigated these biases on automated quality assessments by applying repeated-measures, multivariate ANOVA (rm-MANOVA) on the image quality metrics extracted with MRIQC on the full IXI dataset (N = 581; three acquisition sites). This study found that defacing altered the quality assessments by humans and showed that MRIQC’s quality metrics were mostly insensitive to defacing.

Abstract A seminal study by Triplett provided initial evidence for the social facilitation effect, and over the last century, research has demonstrated this effect across a range of settings. However, despite the importance attributed to Triplett’s study, no research has replicated the original study paradigm. Furthermore, in the context of research advances and methodological rigour, some elements of the original study weaken the validity of the observed findings. We address these critical limitations and replicate the original study, employing a standardized study protocol to minimize potential confounds, such as practice effects. This research reports on 445 school-aged children ( M age = 10.8, SD  = 1.3) who completed the study. As pre-registered in our Stage 1 submission, using a purpose-built apparatus, participants turned a crank to move a marker along a string course between two pulleys. Pairs of participants completed this task four times, twice alone and twice together. Trial order was standardized and balanced to control for possible order/practice effects. In line with Triplett’s original study, we show that participants completed the task faster in the together condition than in the alone condition. We also show interesting variability depending on age and gender, as well as demonstrating “carryover” effects. Thus, we replicate and extend this classic finding, adding to the literature on social facilitation/competitive coaction. In addition, the materials and methods developed here provide a template for future studies to further examine this phenomenon. Protocol registration The Stage 1 protocol for this Registered Report is available at https://osf.io/vsgpq , and appears as accepted in principle by the journal on 10th August 2022.

Introduction Uric acid (UA) is considered as a potential risk factor for coronary heart disease (CHD) and other cardiovascular diseases (CVDs). However, the association between hyperuricemia and the risk of CHD and other cardiovascular outcomes has not been fully clarified. This systematic review and dose-response meta-analysis was conducted to comprehensively the association between hyperuricemia and the risk of CHD or other cardiovascular outcomes in the general population. Methods We systematically searched Medline, Cochrane Library, Embase, and two clinical trial registration databases from inception to June 30, 2025, without restrictions on language or publication status. Only cohort and case-control studies enrolling participants without CHD, other CVDs, or gout at baseline were included. The primary outcome was the association between hyperuricemia and the risk of CHD, and secondary outcomes were the association between hyperuricemia and the risk of fatal and nonfatal CVDs, included CHD death, CVD, CVD death, and myocardial infarction (MI). Risk of bias was assessed using the Risk Of Bias In Non-randomized Studies-of Exposure (ROBINS-E) tool. All statistical analyses were performed using R 4.4.2. We conducted meta-analyses, heterogeneity assessments, publication bias tests, trim-and-fill analyses, subgroup and sensitivity analyses, meta-regressions, and dose-response meta-analyses. The GRADE recommendation was used to evaluate the quality of evidence. Results A total of 42 articles representing 39 individual studies and 1,082,880 participants were included. Among these, 2 articles were assess as “very high risk of bias”, eight as “high risk of bias”, and two as “some concerns”. Hyperuricemia was significantly associated with an increased risk of CHD [HR 1.21 (95%CI 1.14–1.28), p < 0.001, I2 = 34.34%], CHD death [1.20 (1.05–1.36), p = 0.005, I2 = 41.28%], CVD death [1.75 (1.12–2.74), p = 0.014, I2 = 49.48%], and MI [1.23 (1.03–1.47), p = 0.025, I2 = 56.96%]. No significant association was observed for overall CVD risk [1.09 (0.94–1.27), p = 0.245, I2 = 0%]. For each unit increase in serum UA, the risk of CHD, CHD death, CVD, CVD death, and MI increased by 16%, 13%, 12%, 11%, and 7%, respectively. No factors with a significant impact on the results were identified through subgroup analyses or meta-regression. Sex may have a potential influence, but the results were not robust. Further dose-response meta-analysis revealed a linear relationship between higher serum UA and CVD risk, and a U-shaped association between serum UA and CVD mortality in men. The quality of evidence was rated as low for CHD and very low for the other cardiovascular outcomes. Conclusion This systematic review and dose-response meta-analysis provides low- to very-low-quality evidence suggesting that hyperuricemia may be associated with an increased risk of CHD and other fatal or nonfatal CVDs. Trial registration This study was registered in PROSPERO CRD42024538553.

This trial and its outcomes were registered with clinicaltrials.gov on Feb. 7, 2023 under the identifier NCT05718973. The stage 1 protocol for this Registered Report was accepted in principle on 18/09/23. The protocol, as accepted by the journal, can be found at: 10.6084/m9.figshare.24246511.

Stressors like test anxiety are known to decrease memory retrieval, whereas retrieval practice is the phenomenon that actively recalling information from memory enhances memory. Evidence suggests retrieval practice can protect memory against the negative effects of stress on memory (Agarwal et al., 2014; Smith &amp; Thomas, 2018), however the findings are mixed (Yang et al., 2020). Understanding whether retrieval practice maintains memory performance under stress could transform memory resilience and lead to new cognitive interventions. This raises the need for a meta-analytic summary of the literature to understand the effects of retrieval practice on memory in relation to stressors. In this registered report, we conducted a meta-analysis (k = 10, n = 908) on the impact of stress following learning with retrieval practice from 2006&ndash;2024 using databases and other information sources. We found a positive effect of retrieval practice in stress conditions, Hedges&rsquo; g = 0.45, 95% CI [0.17, 0.72] with a random-effects two-level model, suggesting retrieval practice is more beneficial than restudy during stress. Significant heterogeneity was observed along with a moderate risk of bias, yet little evidence for publication bias. We did not find significant moderators in this sample. Future studies should be conducted with sufficiently powered samples and using other types of control, or non-retrieval practice, strategies to better understand the protective effects of retrieval practice on memory following stress. We registered our meta-analysis, with datafile, code and supplementary here: https://osf.io/jwx4f/.

Background: For many years, clinicians have been seeking for objective pain assessment solutions via neuroimaging techniques, focusing on the brain to detect human pain. Unfortunately, most of those techniques are not applicable in the clinical environment or lack accuracy. Objective: This study aimed to test the feasibility of a mobile neuroimaging-based clinical augmented reality (AR) and artificial intelligence (AI) framework, CLARAi, for objective pain detection and also localization direct from the patient’s brain in real time. Methods: Clinical dental pain was triggered in 21 patients by hypersensitive tooth stimulation with 20 consecutive descending cold stimulations (32°C-0°C). We used a portable optical neuroimaging technology, functional near-infrared spectroscopy, to gauge their cortical activity during evoked acute clinical pain. The data were decoded using a neural network (NN)–based AI algorithm to classify hemodynamic response data into pain and no-pain brain states in real time. We tested the performance of several networks (NN with 7 layers, 6 layers, 5 layers, 3 layers, recurrent NN, and long short-term memory network) upon reorganized data features on pain diction and localization in a simulated real-time environment. In addition, we also tested the feasibility of transmitting the neuroimaging data to an AR device, HoloLens, in the same simulated environment, allowing visualization of the ongoing cortical activity on a 3-dimensional brain template virtually plotted on the patients’ head during clinical consult. Results: The artificial neutral network (3-layer NN) achieved an optimal classification accuracy at 80.37% (126,000/156,680) for pain and no pain discrimination, with positive likelihood ratio (PLR) at 2.35. We further explored a 3-class localization task of left/right side pain and no-pain states, and convolutional NN-6 (6-layer NN) achieved highest classification accuracy at 74.23% (1040/1401) with PLR at 2.02. Conclusions: Additional studies are needed to optimize and validate our prototype CLARAi framework for other pains and neurologic disorders. However, we presented an innovative and feasible neuroimaging-based AR/AI concept that can potentially transform the human brain into an objective target to visualize and precisely measure and localize pain in real time where it is most needed: in the doctor’s office. International Registered Report Identifier (IRRID): RR1-10.2196/13594