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In order to realize accurate identification of traffic accidents and accurately mine regional road traffic accident data, a data mining model of regional road traffic accidents based on bat algorithm is proposed. According to the braking force of the vehicle on the horizontal road surface when the regional road traffic accident is about to occur, the accident reproduction model is established, the parameters of the traffic accident trace are determined, the data mining model of the regional road traffic accident is constructed, and finally the bat algorithm is used to solve the problem to realize the regional road traffic accident, data mining. The research results show that the mining results of the proposed model on regional road traffic accident data are consistent with the actual number of samples of regional road traffic accident data. Between 99%, the F1 value is higher than 0.97, and the recognition time of the model is less than 385ms. The performance of the model in this paper is better than the comparison model, and it has application value. [ABSTRACT FROM AUTHOR]

This study examined the influence of trauma exposure and posttraumatic stress (PTS) severity on accuracy of recall of autobiographical memory of traumatic events and pleasant events in very young children. Two hundred sixteen 3–6 year-old children with trauma exposure were interviewed with standardized interviews. Forty-one non-trauma-exposed controls were interviewed about stressful events for comparison. Accuracy of recall for both traumatic and pleasant events was not associated with severity of PTS. Trauma-exposed children showed significantly less accurate recall of trauma events compared to pleasant events. This difference was limited to children who experienced repeated trauma or Hurricane Katrina-related trauma experiences as opposed to single-blow types of trauma experiences. There was no difference in accuracy of recall of trauma events in the trauma-exposed group versus stressful events in the control group. There was also no difference in accuracy of recall of pleasant events between the trauma-exposed and the control groups. These findings do not support traditional theories that autobiographical recall is impaired in those with posttraumatic stress disorder or with trauma exposure. These findings demonstrate that very young children have access to and can verbalize accurate autobiographical recall of trauma events, which is important for clinical assessment and treatment. [ABSTRACT FROM AUTHOR]

Human beings usually rely on communication to express their feeling and ideas and to solve disputes among themselves. A major component required for effective communication is language. Language can occur in different forms, including written symbols, gestures, and vocalizations. It is usually essential for all of the communicating parties to be fully conversant with a common language. However, to date this has not been the case between speech-impaired people who use sign language and people who use spoken languages. A number of different studies have pointed out a significant gaps between these two groups which can limit the ease of communication. Therefore, this study aims to develop an efficient deep learning model that can be used to predict British sign language in an attempt to narrow this communication gap between speech-impaired and non-speech-impaired people in the community. Two models were developed in this research, CNN and LSTM, and their performance was evaluated using a multi-class confusion matrix. The CNN model emerged with the highest performance, attaining training and testing accuracies of 98.8% and 97.4%, respectively. In addition, the model achieved average weighted precession and recall of 97% and 96%, respectively. On the other hand, the LSTM model's performance was quite poor, with the maximum training and testing performance accuracies achieved being 49.4% and 48.7%, respectively. Our research concluded that the CNN model was the best for recognizing and determining British sign language. [ABSTRACT FROM AUTHOR]

It is critical that organizations deliver timely, effective communication about potential risks and life-saving information. The National Weather Service (NWS) developed a suite of messages known as "experimental graphic products" to be automatically distributed through their local official Twitter accounts at the onset of fast-moving, severe weather events such as tornadoes. However, recent research has suggested messages need to be carefully constructed for audiences to place attention to the content, remember the content, and later act in response to the content. The purpose of this study is to explore what people recall of the NWS Twitter message. We used an online survey instrument, distributed via Qualtrics, to investigate participant responses to three open-ended questions about the message. We performed a quantitative analysis to summarize the frequency of message features recorded by participants, and a qualitative analysis to identify themes that provide a deeper description of what was recalled. We found that participants encoded the hazard type, the time the message was sent and would expire, and the types of impacts that might occur. Graphic design cues elicited attention as they "stood out" to the participants. When asked about importance and what they would tell others, respondents described protective action, indicating participants may have activated prior knowledge of the threat, as it was not included in the message. Risk, disaster, and science communicators can draw guidance about communicating during a disaster. It provides a lens for researching message construction, and the importance of communicating protective action guidance during severe weather events. [ABSTRACT FROM AUTHOR]

Information overload is the biggest challenge nowadays for any website - especially e-commerce websites. However, this challenge has arisen due to the fast growth of information on the web (WWW) along with easier access to the internet. A collaborative filtering-based recommender system is the most useful application for solving the information overload problem by filtering relevant information for users according to their interests. However, the current system faces some significant limitations such as data sparsity, low accuracy, cold-start, and malicious attacks. To alleviate the above-mentioned issues, the relationship of trust incorporates in the system where it can be among users or items; such a system is known as a trust-based recommender system (TBRS). From the user perspective, the motive of a TBRS is to utilize the reliability among users to generate more-accurate and trusted recommendations. However, the study aims to present a comparative analysis of different trust metrics in the context of the type of trust definition of TBRS. Also, the study accomplishes 24 trust metrics in terms of the methodology, trust properties & measurements, validation approaches, and the experimented data set. [ABSTRACT FROM AUTHOR]

Introduction: While factors such as age and education have been associated with persistent differences in functional cognitive decline, they do not fully explain observed variations particularly those between different racial/ethnic and sex groups. The aim of this study was to explore the association between allostatic load (AL) and cognition in a racially diverse cohort of young adults., Methods: Utilizing Wave V of the National Longitudinal Study of Adolescent to Adult Health - a nationally representative, longitudinal survey of adults aged 34-44, this study utilized primary data from 10 immune, cardiovascular, and metabolic biomarkers to derive an AL Index. Cognition was previously recorded through word and number recall scores. Regression analysis evaluated the association between cognitive recall, AL, age, sex, and race/ethnicity., Results: Regression results indicated statistically higher AL scores among Blacks (IRR = 1.09, CI = 1.01, 1.19) compared to Whites and lower AL score among females compared to males (IRR = 0.76, CI = 0.72, 0.81). At zero AL, Blacks (IRR = 1.2399, CI = 1.2398, 1.24) and Other races (IRR = 1.4523, CI = 1.452, 1.4525) had higher recall while Hispanics (IRR = 0.808, CI = 0.8079, 0.8081) had lower recall compared to Whites. Relative to males, females had higher number recall (IRR = 1.1976, CI = 1.1976, 1.1977). However, at higher, positive levels of AL, Blacks (IRR = 0.9554, CI = 0.9553, 0.9554), Other races (IRR = 0.9479, CI = 0.9479, 0.9479) and females (IRR = 0.9655, CI = 0.9655, 0.9655) had significantly lower number recall than Whites and males respectively., Conclusions: Race and sex differences were observed in recall at different levels of AL. Findings demonstrate the need for further exploration of cognition in young adults across diverse populations that includes examination of AL.

Despite bilateral hippocampal damage dating to the perinatal or early childhood period and severely impaired episodic memory, patients with developmental amnesia continue to exhibit well-developed semantic memory across the developmental trajectory. Detailed information on the extent and focality of brain damage in these patients is needed to hypothesize about the neural substrate that supports their remarkable capacity for encoding and retrieval of semantic memory. In particular, we need to assess whether the residual hippocampal tissue is involved in this preservation, or whether the surrounding cortical areas reorganize to rescue aspects of these critical cognitive memory processes after early injury. We used voxel-based morphometry (VBM) analysis, automatic (FreeSurfer) and manual segmentation to characterize structural changes in the brain of an exceptionally large cohort of 23 patients with developmental amnesia in comparison with 32 control subjects. Both the VBM and the FreeSurfer analyses revealed severe structural alterations in the hippocampus and thalamus of patients with developmental amnesia. Milder damage was found in the amygdala, caudate, and parahippocampal gyrus. Manual segmentation demonstrated differences in the degree of atrophy of the hippocampal subregions in patients. The level of atrophy in CA-DG subregions and subicular complex was more than 40%, while the atrophy of the uncus was moderate (-24%). Anatomo-functional correlations were observed between the volumes of residual hippocampal subregions in patients and selective aspects of their cognitive performance, viz, intelligence, working memory, and verbal and visuospatial recall. Our findings suggest that in patients with developmental amnesia, cognitive processing is compromised as a function of the extent of atrophy in hippocampal subregions. More severe hippocampal damage may be more likely to promote structural and/or functional reorganization in areas connected to the hippocampus. In this hypothesis, different levels of hippocampal function may be rescued following this variable reorganization. Our findings document not only the extent, but also the limits of circuit reorganization occurring in the young brain after early bilateral hippocampal damage., (© 2024 The Author(s). Hippocampus published by Wiley Periodicals LLC.)

In the landscape of medical device regulation, Class I recalls serve as pivotal indicators of potential risks, necessitating comprehensive analysis to unveil underlying patterns and causal factors. This research offers a detailed examination of Class 1 recalls, focusing on the critical aspects of device classification, review panel involvement, and the geographic distribution of recalling companies. Utilizing a robust dataset spanning multiple jurisdictions and device categories, this study reveals recurring trends in recall occurrences, providing insights into the regulatory mechanisms governing device safety assessments. Furthermore, it investigates the role of review panels in evaluating device safety and effectiveness, shedding light on their significance in the recall process. Moreover, the analysis explores the countries of origin of companies initiating recalls, offering insights into the global impact of regulatory actions on medical device manufacturers. By understanding the drivers behind recall decisions and their implications on a regional scale, regulatory authorities, and healthcare stakeholders can implement targeted measures to enhance patient safety and strengthen post-market surveillance practices., Competing Interests: Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, M.J. et al.)

Drawing a referent of a to-be-remembered word often results in better recognition and recall of this word relative to a control task in which the word is written, a pattern dubbed the drawing effect. Although this effect is not always found in pure lists, we report three experiments in which the drawing effect emerged in both pure- and mixed-lists on recognition and recall tests, though the effect was larger in mixed lists. Our experiments then compared drawing effects on memory between pure- and mixed-list contexts to determine whether the larger mixed-list drawing effect reflected a benefit to draw items, a cost to write items, or a combination. In delayed recognition and free-recall tests, a mixed-list benefit emerged for draw items in which memory for mixed-list draw items was greater than pure-list draw items. This mixed-list drawing benefit was accompanied by a mixed-list writing cost compared to pure-list write items, indicating that the mixed-list drawing effect does not operate cost-free. Our findings of a pure-list drawing effect are consistent with a memory strength account, however, the larger drawing effect in mixed lists suggest that participants may also deploy a distinctiveness heuristic to aid retrieval of drawn items., (© 2024. The Psychonomic Society, Inc.)

Background: Several measures of occupational exposure to pesticides have been used to study associations between exposure to pesticides and neurobehavioral outcomes. This study assessed the impact of different exposure measures for glyphosate and mancozeb on the association with neurobehavioral outcomes based on original and recalled self-reported data with 246 smallholder farmers in Uganda., Methods: The association between the 6 exposure measures and 6 selected neurobehavioral test scores was investigated using linear multivariable regression models. Exposure measures included original exposure measures for the previous year in 2017: (i) application status (yes/no), (ii) number of application days, (iii) average exposure-intensity scores (EIS) of an application and (iv) number of EIS-weighted application days. Two additional measures were collected in 2019: (v) recalled application status and (vi) recalled EIS for the respective periods in 2017., Results: Recalled applicator status and EIS were between 1.2 and 1.4 times more frequent and higher for both pesticides than the original application status and EIS. Adverse associations between the different original measures of exposure to glyphosate and 4 neurobehavioral tests were observed. Glyphosate exposure based on recalled information and all mancozeb exposure measures were not associated with the neurobehavioral outcomes., Conclusions: The relation between the different original self-reported glyphosate exposure measures and neurobehavioral test scores appeared to be robust. When based on recalled exposure measures, associations observed with the original exposure measures were no longer present. Therefore, future epidemiological studies on self-reported exposure should critically evaluate the potential bias towards the null in observed exposure-response associations., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Objectives: Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting., Methods: We systematically searched publications related to EM research and NLP across databases including MEDLINE, Embase, Scopus, CENTRAL, and ProQuest Dissertations & Theses Global. Independent reviewers screened, reviewed, and evaluated article quality and bias. NLP usage was categorized into syndromic surveillance, radiologic interpretation, and identification of specific diseases/events/syndromes, with respective sensitivity analysis reported. Performance metrics for NLP usage were calculated and the overall area under the summary of receiver operating characteristic curve (SROC) was determined., Results: A total of 27 studies underwent meta-analysis. Findings indicated an overall mean sensitivity (recall) of 82%-87%, specificity of 95%, with the area under the SROC at 0.96 (95% CI 0.94-0.98). Optimal performance using NLP was observed in radiologic interpretation, demonstrating an overall mean sensitivity of 93% and specificity of 96%., Conclusions: Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management., (© 2024 The Authors. Academic Emergency Medicine published by Wiley Periodicals LLC on behalf of Society for Academic Emergency Medicine.)

Objectives: Film mammography has been replaced by digital mammography in breast screening programs globally. This led to a small increase in the rate of detection, but whether the detection of clinically important cancers increased is uncertain. We aimed to assess the impact on tumor characteristics of screen-detected and interval breast cancers., Study Design and Setting: We searched seven databases from inception to October 08, 2023, for publications comparing film and digital mammography within the same population of asymptomatic women at population (average) risk of breast cancer. We recorded reported tumor characteristics and assessed risk of bias using the Risk Of Bias In Non-randomised Studies - of Interventions tool. We synthesized results using meta-analyses of random effects., Results: Eighteen studies were included in the analysis from 8 countries, including 11,592,225 screening examinations (8,117,781 film; 3,474,444 digital). There were no differences in tumor size, morphology, grade, node status, receptor status, or stage in the pooled differences for screen-detected and interval invasive cancer tumor characteristics. There were statistically significant increases in screen-detected ductal carcinoma in situ (DCIS) across all grades: 0.05 (0.00-0.11), 0.14 (0.05-0.22), and 0.19 (0.05-0.33) per 1000 screens for low, intermediate, and high-grade DCIS, respectively. There were similar (non-statistically significant) increases in screen-detected invasive cancer across all grades., Conclusion: The increased detection of all grades of DCIS and invasive cancer may indicate both increased early detection of more aggressive disease and increased overdiagnosis., Competing Interests: Declaration of competing interest None declared., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

One of the things that has often been questioned lately is in the field of public services, especially in terms of the quality or service quality of government agencies to the community, the Manpower and Transmigration Office of Kab. Karawang is a government agency in charge of public services. where one of the tasks is to make an AK.1 card (yellow card), based on this problem the Manpower and Transmigration Office of Kab. Karawang Regency. Karawang seeks to improve service quality in order to satisfy consumers by distributing questionnaires to every consumer who is making an AK card.1. In this study, we will apply the C4.5 and Naïve Bayes algorithms to predict the satisfaction of public services with the nominal type of dataset used. The evaluation is done based on a comparison of the level of accuracy, precision, recall, and F-Measure using a confusion matrix. From the research that has been carried out, the Naïve Bayes algorithm with 70% training data distribution and 30% testing is able to provide better predictive results than the C4.5 algorithm as evidenced by the accuracy value = 96.89%, precision = 95.50%, recall = 95.00% and f-measure = 94.60%.

Background We compared results from household data sources to medical record sources by using data from a vaccination coverage survey. Methods Vaccination coverage (VC) was calculated based on parental recall, household vaccination booklet, and Zhejiang provincial immunization information system (ZJIIS). We evaluated the accuracy of VC based on household sources (vaccination booklet and recall) assuming the medical record was accurate. Concordance, sensitivity, specificity, positive predictive value, and negative predictive value were estimated as well as the Kappa statistic was also used to evaluate the agreement between data sources. Results Among the 1,800 children identified in the household survey, all were registered in ZJIIS. VC estimated using the vaccination booklet alone was substantially lower than that based on medical records (net bias 3.4–16.7% in different age groups). VC based on parental recall ranged from 2.5% below (among children aged 1 year) to 16.7% points above (among children aged 6 years) than those based on medical records. Concordance was lowest for card estimates (32.5–45.5%). Sensitivity was 75%, while negative predictive value was

A “Portaria Conjunta” n. 03, de 1/07/2019, do Ministério da Justiça e do Ministério da Infraestrutura, instituiu novas regras para o recall, inclusive com a possibilidade de constar uma observação expressa no certificado de registro do veículo. Previsto a partir do Código de Defesa do Consumidor, em 1990, o instituto do recall representa um fator de respeito aos consumidores por parte de fornecedores que tomam conhecimento de que determinados produtos ou serviços inseridos no mercado de consumo possuem um alto grau de periculosidade. Por meio do recall, os consumidores são informados a respeito da periculosidade de produtos ou serviços adquiridos e são convocados pelos fornecedores para sanar a falha gratuitamente. Apesar da regulamentação do assunto por meio de normas e construções doutrinárias e jurisprudenciais, alguns pontos ainda merecem esclarecimento, tais como a necessidade de fixação de um prazo para o chamamento e a delimitação da responsabilidade do fornecedor em casos de não atendimento pelo consumidor do prazo fixado para recall.

Abstract In this study, a method for a robot to recall multiple grasping methods for a given object is proposed. The aim of this study was for robots to learn grasping methods for new objects by observing the grasping activities of humans in daily life without special instructions. For this setting, only one grasping motion was observed for an object at a time, and it was never known whether other grasping methods were possible for the object, although supervised learning generally requires all possible answers for each training input. The proposed method gives a solution for that learning situations by employing a convolutional neural network with automatic clustering of the observed grasping method. In the proposed method, the grasping methods are clustered during the process of learning of the grasping position. The method first recalls grasping positions and the network estimates the multi-channel heatmap such that each channel heatmap indicates one grasping position, then checks the graspability for each estimated position. Finally, the method recalls the hand shapes based on the estimated grasping position and the object’s shape. This paper describes the results of recalling multiple grasping methods and demonstrates the effectiveness of the proposed method.

Abstract Evidence suggests that memory is involved in making simulations and predictions about the future (i.e., future thinking), but less work has examined how the outcome of those predictions (whether events play out as predicted or expected) subsequently affects episodic memory. In this investigation, we examine whether memory is better for outcomes that are consistent with predictions, or whether memory is enhanced for outcomes that are inconsistent with predictions, after the predicted event occurs. In this experiment, participants learned a core trait associated with social targets (e.g., high in extroversion), before making predictions about behaviors targets would perform. Participants then were shown behaviors the social targets actually performed (i.e., prediction outcome), which was either consistent or inconsistent with predictions. After that, participants completed a memory test (recognition; recall) for the prediction outcomes. For recognition, the results revealed better memory for outcomes that were consistent with traits associated with targets (i.e., trait‐consistent outcomes), compared to outcomes that were inconsistent (i.e., trait‐inconsistent outcomes). Finding a memory advantage for trait‐consistent outcomes suggests that outcomes that are in line with the contents of memory (e.g., what one knows; schemas) are more readily remembered than those that are inconsistent with memory, which may reflect an adaptive memory process. For recall, memory did not differ between trait‐consistent and trait‐inconsistent outcomes. Altogether, the results of this experiment advance understanding of the reciprocal relationship between episodic memory and future thinking and show that outcome of predictions has an influence on subsequent episodic memory, at least as measured by recognition.

The aim of this study was to test claims that speakers of a first language (L1) incur cognitive and linguistic processing costs when interacting with second language (L2) speakers. This is thought to be due to the extra cognitive effort required for mapping incoming L2 speech signals onto stored phonological, lexical and semantic representations. Recent work suggests that these processing costs may lead to poorer memory of not only the L2 speech, but of one's own produced speech during an interaction with an L2 speaker. Little is known about whether this is also moderated by working memory (WM) capacity and/or the L2 interlocutor's proficiency. In a partial replication study of Lev-Ari et al., 54 healthy L1 English participants performed a WM test and then read a story and answered inference questions about it from a confederate in one of three conditions: the confederate was either a) a fellow L1 speaker; b) a Chinese L2 speaker of English with advanced proficiency or c) a Chinese L2 speaker of English with intermediate proficiency. Following a distractor task, participants were asked to recall their own answers in a surprise response-recognition questionnaire. Participants recognized their responses more accurately after interacting with the L1 speaker compared with the advanced L2 speaker but not compared with the intermediate L2 speaker. WM capacity correlated with higher accuracy when interacting with the L1 speaker, but with lower accuracy when interacting with the intermediate L2 speaker. These results suggest that effortful processing of input may lead to fuzzier lexical and/or semantic representations of one's own produced speech. However, the lack of significance in recall accuracy between the L1 and the intermediate L2 condition suggests other factors may be at play. Qualitative analyses of the conversations provided insights into strategies that individuals adopt to reduce cognitive load and achieve successful communication.

Introduction: Statins are a class of lipid lowering medications, which can effectively lower cardiovascular mortality and morbidity by the beneficial effects in atherosclerotic cardiovascular disease. Recently, there are increasing concerns over the relationship between statins and cognitive deficits. On the contrary, some studies have indicated an improvement in memory functions with the use of statins. However, the impact of statins on cognition is still unclear. Aim: To analyse the effect of statins on cognition and memory using Mini-Mental Scale Examination (MMSE). Materials and Methods: The case-control study was conducted in Department of Cardiology at PSG Institute of Medical Sciences and Research, Coimbatore, Tamil Nadu, India (tertiary care teaching hospital), from June 2019 to December 2019. Out of total 127 participants, case group included 63 adult patients of both genders, on statin therapy for at least 12 weeks duration and control group included 64 age and gender matched adults who were not on statin therapy. After obtaining a written informed consent, MMSE questionnaire was administered by a trained blinded interviewer to both groups. Pearson’s correlation was performed to evaluate any significant correlation between duration of statin therapy with MMSE and individual domain scores. Data was analysed using Statistical Package for Social Sciences (SPSS) version 24.0, and p-value

The primary research purpose lies in studying the intelligent detection of movements in basketball training through artificial intelligence (AI) technology. Primarily, the theory of somatosensory gesture recognition is analyzed, which lays a theoretical foundation for research. Then, the collected signal is denoised and normalized to ensure that the obtained signal data will not be distorted. Finally, the four algorithms, decision tree (DT), naive Bayes (NB), support vector machine (SVM), and artificial neural network (ANN), are used to detect the data of athletes' different limb movements and recall. The accuracy of the data is compared and analyzed. Experiments show that the back propagation (BP) ANN algorithm has the best action recognition effect among the four algorithms. In basketball training athletes' upper limb movement detection, the average accuracy rate is close to 93.3%, and the average recall is also immediate to 93.3%. In basketball training athletes' lower limb movement detection, the average accuracy rate is close to 99.4%, and the average recall is immediate to 99.4%. In the detection of movements of upper and lower limbs: the recognition method can efficiently recognize the basketball actions of catching, passing, dribbling, and shooting, the recognition rate is over 95%, and the average accuracy of the four training actions of catching, passing, dribbling, and shooting is close to 98.95%. The intelligent basketball training system studied will help basketball coaches grasp the skilled movements of athletes better to make more efficient training programs and help athletes improve their skill level. [ABSTRACT FROM AUTHOR]

Challenges to verbal encoding may affect the ability of autistic individuals to express their ideas. Therefore, visuospatial expression may represent a person's knowledge and skills more accurately than spoken language. To test this hypothesis, we asked seven autistic adults to linguistically retell and visuospatially reenact several animated clips. On average, visuospatial responses contained more correct elements than spoken responses. The level of intention of the three stimulus categories did not systematically affect response accuracy. Participants who produced visuospatial responses before spoken responses and those who had watched a greater number of stimuli assigned higher intentionality to shapes in the animations that were designed to elicit mentalizing. The modality used for expression may affect accuracy of responses by autistic individuals. [ABSTRACT FROM AUTHOR]

Although autism spectrum disorders (ASD) are commonly characterized by diminished episodic memory, the literature in this area is mixed. We address these inconsistent findings by employing multilevel Bayesian meta-analysis to quantify episodic memory differences between individuals with ASD and typically developing (TD) controls. We used meta-regression to evaluate the effects of test modality (e.g., word list, story recall), delay interval (immediate vs. delayed), retrieval demands (recognition vs. recall), and sensory modality (auditory vs. visual) on episodic memory in ASD. A total of 338 effect sizes from 113 empirical articles, including 5,632 unique participants (ASD = 2,777, TD = 2,855), were included. Results show that the memory deficits associated with ASD were larger for recall (g = -0.52, se = 0.04, 95% CrI [-0.60, -0.43]) compared to recognition (g = -0.25, se = 0.05, 95% CrI [-0.35, -0.14]) and differed based on the testing modality. For example, effect sizes were smallest for words (g = -0.28, se = 0.05, 95% CrI [-0.38, -0.18]), pictures (g = -0.38, se = 0.07, 95% CrI [-0.52, -0.24]), and figure reproduction (g = -0.49, se = 0.11, 95% CrI [-0.70, -0.27]). However, effect sizes for sentences (g = -0.59, se = 0.20, 95% CrI [-1.00, -0.21]), stories (Hedges' g = -0.54, se = 0.08, 95% CrI [-0.69, -0.38]) and staged events (g = -0.75, se = 0.10, 95% CrI [-0.95, -0.55]) were much larger. These findings suggest that ASD is associated with a small to medium reduction in scores on episodic memory tests relative to TD controls. [ABSTRACT FROM AUTHOR]