Positive Effect Research Articles

Enhanced patient-based real-time quality control using the graph-based anomaly detection.

Patient-based real-time quality control (PBRTQC) is an alternative tool for laboratories that has gained increasing attention. Despite the progress made by using various algorithms, the problems of data volume imbalance between in-control and out-of-control results, as well as the issue of variation remain challenges. We propose a novel integrated framework using anomaly detection and graph neural network, combining clinical variables and statistical algorithms, to improve the error detection performance of patient-based quality control. The testing results of three representative analytes (sodium, potassium, and calcium) and eight independent variables of patients (test date, time, gender, age, department, patient type, and reference interval limits) were collected. Graph-based anomaly detection network was modeled and used to generate control limits. Proportional and random errors were simulated for performance evaluation. Five mainstream PBRTQC statistical algorithms were chosen for comparison. The framework of a patient-based graph anomaly detection network for real-time quality control (PGADQC) was established and proven feasible for error detection. Compared with classic PBRTQC, the PGADQC showed a more balanced performance for both positive and negative biases. For different analytes, the average number of patient samples until error detection (ANPed) of PGADQC decreased variably, and reductions could reach up to approximately 95 % at a small bias of 0.02 taking calcium as an example. The PGADQC is an effective framework for patient-based quality control, integrating statistical and artificial intelligence algorithms. It improves error detection in a data-driven fashion and provides a new approach for PBRTQC from the data science perspective.

Comparison between supervised and physics-informed unsupervised deep neural networks for estimating cerebral perfusion using multi-delay arterial spin labeling MRI.

This study aimed to implement a physics-informed unsupervised deep neural network (DNN) to estimate cerebral blood flow (CBF) and arterial transit time (ATT) from multi-delay arterial spin labeling (ASL), and compare its performance with that of a supervised DNN and the conventional method. Supervised and unsupervised DNNs were trained using simulation data. The accuracy and noise immunity of the three methods were compared using simulations and in vivo data. The simulation study investigated the differences between the predicted and ground-truth values and their variations with the noise level. The in vivo study evaluated the predicted values from the original images and noise-induced variations in the predicted values from the synthesized noisy images by adding Rician noise to the original images. The simulation study showed that CBF estimated using the supervised DNN was not biased by noise, whereas that estimated using other methods had a positive bias. Although the ATT with all methods exhibited a similar behavior with noise increase, the ATT with the supervised DNN was less biased. The in vivo study showed that CBF and ATT with the supervised DNN were the most accurate and that the supervised and unsupervised DNNs had the highest noise immunity in CBF and ATT estimations, respectively. Physics-informed unsupervised learning can estimate CBF and ATT from multi-delay ASL signals, and its performance is superior to that of the conventional method. Although noise immunity in ATT estimation was superior with unsupervised learning, other performances were superior with supervised learning.

Derive the biased reading of <i>A-not-A</i> questions in Mandarin

Among many forms of A-not-A questions in Mandarin Chinese, the shi-not-shi question is found to be unique in that it obligatorily gives rise to a biased reading toward its prejacent, so-called positive bias. The previous pragmatic approach by Ye (2020) establishes a link between focus in polar questions and question bias to explain this biased reading. However, the current study finds that two other A-not-A questions formed by epistemic modals, hui-not-hui and keneng-not-keneng which are not focus markers, obligatorily produce positively biased readings as well. I propose that biased A-not-A questions are a type of high-negation questions with A-not-A residing outside of TP. shi, hui and keneng should all be analyzed as epistemic modals which are the overt realization of Goodhue’s (2019) epistemic operator scoped by the negator. The positively biased reading is derived from the resulting unbalanced partition based on general pragmatic principles. This analysis from the semantic aspect provides new evidence for the argument that the first A has reality only in PF. Furthermore, the Mandarin Chinese data lends evidence to Goodhue’s (2019) argument that there exists a doxastic speech operator between NegP and TP in high negation questions. The paper also provides explanations for previously remaining questions on bias cancelation by the stress marker daodi and factive predicates like zhidao (“know”).

Intimate Care Products and Incidence of Hormone-Related Cancers: A Quantitative Bias Analysis.

Intimate care products may contain substances associated with increased risk of hormone-related cancers. The relationship between genital talc use and ovarian cancer, in particular, has been well studied, but concerns about recall bias and exposure misclassification have precluded conclusions. We examined the association between intimate care products and female hormone-related cancers, accounting for potential biases, using data from a US-based cohort study. The Sister Study enrolled 50,884 women who had a sister with breast cancer. Data on genital talc use and douching were collected at enrollment (2003-2009) and follow-up (2017-2019). We used Cox proportional hazards models to estimate hazard ratios (HRs) for associations between intimate care product use and breast, ovarian, and uterine cancers. To account for potential exposure misclassification and recall bias, we conducted quantitative bias analyses under various exposure reassignment assumptions. Across considered scenarios, 41%-64% of participants douched and 35%-56% used genital talc. In models adjusted for exposure misclassification, genital talc use was positively associated with ovarian cancer (HR range, 1.17-3.34) Frequent douching and douching during young adulthood were positively associated with ovarian cancer, but neither douching nor talc was associated with breast or uterine cancer. Differential reporting of talc use by cases and noncases likely produces positive biases, but correcting for error still resulted in HRs above 1.0. For example, HR, 1.40 (95% CI, 1.04 to 1.89) when 25% of exposed cases and 10% of unexposed noncases had talc status reassigned. Although results show how differential recall would upwardly bias estimates, corrected results support a positive association between use of intimate care products, including genital talc, and ovarian cancer.

Distribution and use of tax support for housing in the Czech Republic

AbstractThis article focuses on mortgage interest deduction (MID) as an indirect tax support for acquiring one's housing. This form of support is the most widely used in the Czech Republic compared to other tax reliefs and causes the highest losses for the government budget. This paper provides quantitative evidence on how the MID was distributed among taxpayers in the Czech Republic in the period 2008–2019 in relation to taxable income and revenue losses for the government budget. Furthermore, it assesses the effectiveness of these tax measures in reducing socioeconomic inequalities among taxpayers. Research based on the application of the MID in tax returns has shown the effective distribution of the MID until 2017. Tax support for housing was used mainly by taxpayers with low taxable income, which is also the largest group. The essence of vertical equity has been fulfilled, which contributed to reducing the level of social inequality. This positive distributional effect has diminished over time. As of 2019, the highest share of public expenditure was redistributed to taxpayers with higher taxable income, indicating the existence of inequalities in the tax system. The different developments over time have shown that the use of the mortgage interest deduction cannot be assessed statically, as it evolves dynamically over time.

Efficacy of occupational rehabilitation in return to work for back pain: A systematic literature review.

Currently, there is no standard procedure for a return to work (RTW) rehabilitation program used by practitioners. The aim is to investigate the efficacy of occupational rehabilitation programs for workers with back pain. Two independent reviewers screened abstracts and full-text articles in a systematic literature search in three databases conducted in 2023. Subsequently, they extracted data according to the PRISMA Statement. Among the 4,010 articles retrieved, 20 met the inclusion criteria. Data from accepted studies were abstracted into tables relating to the RTW, improvement of pain intensity, quality of life (QOL), and degree of disability in persons with back pain. The risk of bias was assessed using the (SIGN)-criteria. Significant improvements in RTW were shown by a workplace intervention with a physical approach and a multidisciplinary intervention but with a wide range of effect sizes. Five studies showed significant improvements in pain intensity and QOL, six studies observed significant improvements in disability. The studies that stated positive effects on work-related data differed between intervention programs and traditional care. A combination of activity, maintenance therapy, stretching, and manual therapy showed promising results in improving RTW. In addition, the relationship and mediation between employer/workplace and employee seems to be an important aspect of RTW. However, pain intensity, disability, and QOL were enhanced with interventions that included a high proportion of physical activity. However, the intervention programs differed widely, leading to the assumption that the treatment effect of the intervention programs is not established, yet.

Evaluation of soil temperature in CMIP6 multimodel simulations

Soil temperature plays a crucial role in understanding land-atmosphere interactions. The Sixth Phase of Coupled Model Intercomparison Project (CMIP6) provides valuable information on soil temperature, however, the performance of these models in capturing soil temperature variations remains unclear. To comprehensively assess the performance of CMIP6 in simulating soil temperature, we employed a set of in-situ observation data, observation-derived gridded data (TS-GCB) and reanalysis data (ERA5L) to build various evaluating metrics for the surface (0–5 cm) and subsurface (5–15 cm) soils. At the global scale, the multimodel ensemble mean (MME) of CMIP6 generally captured the spatial, annual and seasonal variations of soil temperature, but overestimated measured soil temperature by 1.86 °C (vs. TS-GCB, surface) and 2.16 °C (vs. TS-GCB, subsurface), indicating more heat accumulated in soils than the reality. Surface soil temperature was better represented by MME compared to the subsurface soil layer (vs. TS-GCB). In addition, we found the largest simulation bias in the tropical zone, and both positive and negative bias in the arid regions. The large model spread of the individual models in representing soil temperatures in cold regions or periods highlights the needs of improved understanding of how snow and freeze-thaw affect soil thermal dynamics. Overall, the performance of MME is superior to that of the majority of individual models (vs. TS-GCB). Locally, the large discrepancy among observation-derived data, reanalysis data and CMIP6 simulations suggested that it is imperative to acquire more ground-truth soil temperature to better inform model simulation and forecasting.

Fruits of Emblica officinalis Linn. and its Phytochemicals in the Prevention of Ethanol-induced Hepatotoxicity: A Mini-Review

Abstract:: Excessive alcohol consumption over time is one of the primary causes of liver disease and death globally. Because there is no effective treatment, the situation has become more complicated, and the emphasis has shifted to the use of alternative and complementary medicine to treat liver problems. Herbs with dietary use have played an important part in the treatment of liver diseases since antiquity. Amla or Indian gooseberry, scientifically known as Phyllanthus emblica or Emblica officinalis, is a fruiting plant of the Phyllanthaceae family that is used in a variety of traditional and folk medical systems. The fruits have both dietary and medicinal value and are used to prevent chemical-induced hepatocarcinogenesis and reduce experimentally induced hyperlipidemia and metabolic syndrome in laboratory animals. They also have hepatoprotective effects against a variety of hepatotoxins such as heavy metals, iron overload, ochratoxins, hexachlorocyclohexane, carbon tetrachloride, therapeutic drugs such as paracetamol, and antitubercular. Amla fruits and phytochemicals such as quercetin, gallic acid, ellagic acid, and kaempferol are known to reduce ethanol-induced liver damage, and mechanistic studies have shown that the beneficial effects of these phytochemicals are mediated in part by free radical scavenging, antioxidant, and anti-inflammatory effects. This review examines the positive effects of amla fruit and its phytochemicals for the first time, as well as the mechanisms underlying the protective effects.

Consistency of Aerosol Optical Properties between MODIS Satellite Retrievals and AERONET over a 14-Year Period in Central–East Europe

Aerosols influence Earth’s climate by interacting with radiation and clouds. Remote sensing techniques aim to enhance our understanding of aerosol forcing using ground-based and satellite retrievals. Despite technological advancements, challenges persist in reducing uncertainties in satellite remote sensing. Our study examines retrieval biases in MODIS sensors on Terra and Aqua satellites compared to AERONET ground-based measurements. We assess their performance and the correlation with the AERONET aerosol optical depth (AOD) using 14 years of data (2010–2023) from 29 AERONET stations across 10 Central–East European countries. The results indicate discrepancies between MODIS Terra and Aqua retrievals: Terra overestimates the AOD at 16 AERONET stations, while Aqua underestimates the AOD at 21 stations. The examination of temporal biases in the AOD using the calculated estimated error (ER) between AERONET and MODIS retrievals reveals a notable seasonality in coincident retrievals. Both sensors show higher positive AOD biases against AERONET in spring and summer compared to fall and winter, with few ER values for Aqua indicating poor agreement with AERONET. Seasonal variations in correlation strength were noted, with significant improvements from winter to summer (from R2 of 0.58 in winter to R2 of 0.76 in summer for MODIS Terra and from R2 of 0.53 in winter to R2 of 0.74 in summer for MODIS Aqua). Over the fourteen-year period, monthly mean aerosol AOD trends indicate a decrease of −0.00027 from AERONET retrievals and negative monthly mean trends of the AOD from collocated MODIS Terra and Aqua retrievals of −0.00023 and −0.00025, respectively. An aerosol classification analysis showed that mixed aerosols comprised over 30% of the total aerosol composition, while polluted aerosols accounted for more than 22%, and continental aerosols contributed between 22% and 24%. The remaining 20% consists of biomass-burning, dust, and marine aerosols. Based on the aerosol classification method, we computed the bias between the AERONET AE and MODIS AE, which showed higher AE values for AERONET retrievals for a mixture of aerosols and biomass burning, while for marine aerosols, the MODIS AE was larger and for dust the results were inconclusive.

Attaining quantitatively fewer defects in close-packed InGaZnO synthesized using atomic layer deposition

Owing to their uniformity across large areas, low-temperature processability, and low off-current characteristics, oxide semiconductors demonstrate significant potential for integration into displays, memories, and logic devices. In the hyper scaling era, atomic layer deposition (ALD) is well suited for downsizing device fabrication, leveraging self-limiting chemical reactions to provide nanoscale control, and conformal coating on substrates with high aspect ratios. Hence, in this study, we fabricated highly oriented c-axis-aligned crystalline (CAAC) indium-gallium-zinc oxide (IGZO) thin films using plasma-enhanced ALD (PEALD), introducing an additional thermodynamic driving force for crystallization. A comparative study was conducted on the properties of CAAC-IGZO in correspondence to conventional sputter-based IGZO. In particular, photo-induced current transient spectroscopy (PICTS) is employed to map the electronic structure (density of states (DOS)) of the films, which quantitatively confirmed fewer defects in CAAC-IGZO. Fewer defects result in highly stable CAAC-IGZO transistors with positive bias stress threshold (PBTS) at 0.03 V and negative bias stress threshold (NBTS) at - 0.06 V. Thus, this research on thermally and electrically stable CAAC-IGZO synthesized at low temperatures through PEALD offers insights into the processing and material perspectives for the application of oxide semiconductors in 3D integration.

Effect of Bias Potential on the Interface of a Solid Electrolyte and Electrode during XPS Depth Profiling Analysis.

Depth profiling is an essential method to investigate the physical and chemical properties of a solid electrolyte and electrolyte/electrode interface. In conventional depth profiling, various spectroscopic tools such as X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectroscopy (SIMS) are utilized to monitor the chemical states along with ion bombardment to etch a sample. Nevertheless, the ion bombardment during depth profiling results in an inevitable systematic error, i.e., the accumulation of mobile ions at the electrolyte/electrode interface, known as the ion pile-up phenomenon. Here, we propose a novel method using bias potential, the substrate-bias method, to prevent the ion pile-up phenomena during depth profiling of a solid electrolyte. When the positive bias potential is applied on the substrate (electrode), the number of accumulating ions at the electrolyte/electrode interface is significantly reduced. The in-depth XPS analysis with the biased electrode reveals not only the suppression of the ion pile-up phenomena but also the altered chemical states at the interfacial region between the electrolyte and electrode depending on the bias. The proposed substrate-bias method can be a good alternative scheme for an efficient yet precise depth profiling technique for a solid electrolyte.

Effects of ebselen addition on emotional processing and brain neurochemistry in depressed patients unresponsive to antidepressant medication

Lithium is an effective augmenting agent for depressed patients with inadequate response to standard antidepressant therapy, but numerous adverse effects limit its use. We previously reported that a lithium-mimetic agent, ebselen, promoted a positive emotional bias—an indicator of potential antidepressant activity in healthy participants. We therefore aimed to investigate the effects of short-term ebselen treatment on emotional processing and brain neurochemistry in depressed patients with inadequate response to standard antidepressants. We conducted a double-blind, placebo-controlled 7-day experimental medicine study in 51 patients with major depressive disorder who were currently taking antidepressants but had an inadequate response to treatment. Participants received either ebselen 600 mg twice daily for seven days or identical matching placebo. An emotional testing battery, magnetic resonance spectroscopy and depression and anxiety rating scales were conducted at baseline and after seven days of treatment. Ebselen did not increase the recognition of positive facial expressions in the depressed patient group. However, ebselen increased the response bias towards fear emotion in the signal detection measurement. In the anterior cingulate cortex, ebselen significantly reduced the concentrations of inositol and Glx (glutamate+glutamine). We found no significant differences in depression and anxiety rating scales between visits. Our study did not find any positive shift in emotional bias in depressed patients with an inadequate response to antidepressant medication. We confirmed the ability of ebselen to lower inositol and Glx in the anterior cingulate cortex. These latter effects are probably mediated through inhibition of inositol monophosphatase and glutaminase respectively.

Comparison of the Friedewald and Vujovic methods with the calculated LDL concentration in a biochemical auto-analyzer.

To compare the concentration of Low-Density Lipoprotein (LDL-c) obtained using the Friedewald formula with those obtained directly with the RAYTO CHEMRAY 120 autoanalyzer. Cross-sectional study. We evaluated outpatients with a medical request for a lipid profile study (total cholesterol, triglycerides, LDL, and HDL). The analyses were carried out in a RAYTO CHEMRAY 120 autoanalyzer under the principle of spectrophotometry. We obtained LDL-c using the Friedewald and Vujovic formulas. We evaluated 199 individuals whose direct LDL concentration averages were measured by the RAYTO CHEMRAY 120 equipment. Those calculated by the Friedewald and Vujovic formulas were 129.97 ± 32.66, 119.28 ± 30.44, and 127.01 ± 32.01, respectively, and in all cases, significant differences (P < 0.001) were observed with the RAYTO analyzer. In both cases a low positive bias was found with the RAYTO analyzer.. The Passing-Bablok and Deming's regressions showed a linear correlation between both methods (Friedewald and Vujovic) with the LDL values obtained with the Rayto autoanalyzer. Our study found that the Friedewald and Vujovic methods are good predictors of LDL cholesterol levels and have a low level of bias. Therefore, they could be used as potential predictors.

PENGARUH KEIKUTSERTAAN DALAM KEGIATAN EKSTRAKURIKULER TERHADAP PRESTASI BELAJAR MELALUI KEDISIPLINAN BELAJAR SISWA SEKOLAH MENENGAH ATAS

This study explores the impact of student participation in extracurricular activities on learning achievement mediated by learning discipline. This research was conducted at SMA Negeri 1 Seberida, Indragiri Hulu Regency, with a sample of 30 students in class XI IPS. This research uses a quantitative approach with descriptive quantitative research type, the data analysis used to test the hypothesis is path analysis. The results showed that extracurricular activities have a positive but insignificant direct and indirect effect on learning achievement mediated by student discipline. The results of this study confirm previous research which states that there is a positive and significant effect of participation in extracurricular activities on discipline and learning achievement. However, this study was able to show that discipline and learning achievement can be controlled by school management policies in maintaining student discipline and achievement.

PENGARUH CSR TERHADAP KINERJA KEUANGAN PERUSAHAAN DENGAN UKURAN PERUSAHAAN SEBAGAI VARIABEL MODERATING

This study aims to determine the effect of Corporate Social Responsibility (CSR) on company financial performance as proxied by Return On Assets, Return On Equity, and Net Profit Margin moderated by company size partially in mining sector companies listed on the Indonesia Stock Exchange.The research population includes all mining sector companies listed on the Indonesia Stock Exchange for the 2018-2021 period. The sample in this study was determined by purposive sampling method. The data analysis technique in this research is descriptive and verification. Hypothesis testing uses the Structural Equation Modeling Partial Least Square (SEM-PLS) analysis model. The results of the study show that (1) Corporate Social Responsibility has a positive and significant effect on Return On Assets. (2) Corporate Social Responsibility has no effect on Return On Equity. (3) Corporate Social Responsibility has a positive and significant effect on Net Profit Margin. (4) Company size weakens the effect of the relationship between Corporate Social Responsibility on Return On Assets. (5) Company size weakens the effect of the relationship between Corporate Social Responsibility on Return On Equity. (6) This is indicated by the p-value of Net Profit Margin.

Multilevel resistive switching in hydrothermally synthesized FeWO4 thin film-based memristive device for non-volatile memory application

The memristors offer significant advantages as a key element in non-volatile and brain-inspired neuromorphic systems because of their salient features such as remarkable endurance, ability to store multiple bits, fast operation speed, and extremely low energy usage. This work reports the resistive switching (RS) characteristics of the hydrothermally synthesized iron tungstate (FeWO4) based thin film memristive device. The detailed physicochemical analysis was investigated using Rietveld’s refinement, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) techniques. The fabricated Ag/FWO/FTO memristive device exhibits bipolar resistive switching (BRS) behavior. In addition, the devices exhibit negative differential resistance (NDR) at both positive and negative bias. The charge-flux relation portrayed the non-ideal or memristive nature of the devices. The reliability in the RS process was analyzed in detail using Weibull distribution and time series analysis techniques. The device exhibits stable and multilevel endurance and retention characteristics which demonstrates the suitability of the device for the high-density non-volatile memory application. The current conduction of the device was dominated by Ohmic and trap controlled-space charge limited current (TC-SCLC) mechanisms and filamentary RS process responsible for the BRS in the device. In a nutshell, the present investigations reveal the potential use of the iron tungstate for the fabrication of memristive devices for the non-volatile memory application.

Exploring the Impact of Socioeconomic and Natural Factors on Pulmonary Tuberculosis Incidence in China (2013-2019) using Explainable Machine Learning: A Nationwide Study

Pulmonary tuberculosis (PTB) stands as a significant and prevalent infectious disease in China. Integrating 13 natural and socioeconomic factors, we conduct nine machine learning (ML) models alongside the Tree-Structured Parzen Estimator to predict the monthly PTB incidence rate from 2013 to 2019 in mainland China. With explainable ML techniques, our research highlights that population size, per capita GDP, and PM10 concentration emerge as the primary determinants influencing the PTB incidence rate. We delineate both the independent and interactive impacts of these factors on the PTB incidence rate. Furthermore, crucial thresholds associated with factors influencing the PTB incidence rate are identified. Taking factors that have a positive effect on reducing the incidence rate of PTB as an example, the thresholds at which the effects of factors PM2.5, PM10, O3, and RH on the incidence rate change from increase to decrease are 105.5 μg/m3, 75.5 μg/m3, 90.8 μg/m3, and 72.3% respectively. Our work will contribute valuable insights for public health interventions.

Predicting Intention for Food Safety Behavior among Food Handlers: A Cross-sectional Study in Indonesia’s Beach Culinary Area

Background: The food safety behavior of food handlers constitutes the main factor in foodborne disease control. According to the Theory of Planned Behavior, behavior is determined by the intention that is established from a combination of attitudes, subjective norms, and perceived behavioral control. This research aimed to predict the intention for food safety behavior using the Theory of Planned Behavior. Methods: A cross-sectional study was conducted for two months in the Bantul beach culinary area, Yogyakarta, Indonesia. The research population consisted of 80 food handlers representative of all existing seafood stalls. The respondents were interviewed face-to-face using a paper-based questionnaire related to attitudes, subjective norms, perceived behavioral control, and intention. The data collected were evaluated using structural equation model-partial least square (SEM-PLS), version 3.0, with a sig. level of 0.05. Results: This research successfully predicted 64.3% of the variance in the intention for food safety behavior of food handlers (R2 adjusted = 0.643). The variable-perceived behavioral control was the strongest and most significant predictor, with a positive effect on intention for food safety behavior (β = 0.560, p = 0.000 &lt; 0.05), followed by the variable subjective norms (β = 0.275, p = 0.001 &lt; 0.05). The variable attitude was the weakest predictor, with an insignificant positive effect (β = 007.0, p = 0.182 &gt; 0.05). Conclusion: This research successfully predicted the intention for food safety behavior of food handlers in the Bantul beach culinary area, Yogyakarta, Indonesia.

Mathematics belief impact on metacognition in solving geometry: Middle school students

Mathematical beliefs and metacognitive knowledge play significant roles in solving mathematical problems; thus, this study aims to investigate the influence of middle school students' beliefs on their metacognitive knowledge when solving geometry problems. This study utilizes both quantitative and qualitative research methods. A linear regression test was used to determine the effect of middle school students' beliefs on their metacognitive knowledge. The results of the quantitative research analysis were followed up with a qualitative research approach to describe the metacognitive knowledge of students who have high and low confidence in solving geometric problems. This research involved 352 middle school students in the Tarakan area. Based on the results of linear regression, it is known that the beliefs of middle school students have a positive effect on their metacognitive knowledge when solving geometric problems. In addition, it was found that students with different beliefs could solve a given geometry problem, but the approach to solving it varied among subjects. Middle school students have diverse beliefs, but these variations do not affect their capacity to apply their metacognitive knowledge at every stage of solving mathematical problems.

Collectives closer to the self are anticipated to have a brighter future: Self-enhancement in collective cognition.

Collective future thinking is a budding research field concerned with the act of imagining possible events in the future of a collective-typically one's nation. Prior research has shown that people imagine more positive than negative events in the personal future but more negative than positive events in the collective future. This interaction has been interpreted as a valence-based dissociation between collective and personal cognition. We examine if degrees of self-relatedness may account for these effects. In Study 1, participants (N = 299) imagined events in the future of their country and family, rated how central they viewed these collectives to their self and identity and rated the collectives' futures for positive and negative valence. Positive and negative valence of the imagined collective futures was strongly associated with how central the collectives were viewed to the self. In Study 2, participants (N = 306) rated self-centrality, personal agency, and moral decline perceived for their country. All three measures explained independent variance in how positive the future was for their country. In Study 3, participants (N = 310) self-nominated collectives that they viewed as highly versus minimally central to their self and identity. The futures of highly central collectives were rated more positive than negative, whereas such positive bias was absent for the futures of minimally self-central collectives. Overall, the findings indicate that a continuum of different degrees of self-relatedness may explain the Valence × Domain interaction in previous work, and suggest a need to integrate research on collective future thinking with self-serving biases in social cognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).