Informant Discrepancies Research Articles

A matter of time: Publication dates in Scopus

Similar to the Web of Science, Scopus is also a widely used abstract and citation database. Researchers typically employ the Year of Publication or Date of Publication field in Scopus to retrieve, filter and analyse indexed records. However, the inconsistent retrieval results obtained by these two fields in Scopus, which was occasionally observed in this study, may cause confusion among users. In this brief research article, we seek to elucidate this phenomenon by utilising indexed records in Scopus from the past 50 years. Empirical evidence indicates that inconsistent retrieval results retrieved by these two search fields are attributable to discrepancies in the publication year information provided in the Year of Publication and Date of Publication fields in Scopus. Specifically, missing year information in the Date of Publication field, incorrect year information in the Date of Publication field or in the Year of Publication field, and inconsistent use of different versions of publication dates in these two fields are four representative causes for the observed inconsistencies in retrieval results in Scopus. This article concludes by outlining the potential consequences of these issues and suggesting ways to effectively address them.

Informant discrepancy profiles of helicopter parenting and adult children's partner-controlling and partner-controlled behaviors.

Helicopter parenting is a distinctive, intrusive parenting approach characterized by high involvement, elements of control, and limited autonomy granted. It may impact adult children's engagement in partner-controlling and partner-controlled behaviors. However, little research has assessed the patterns of parent-child perception differences regarding helicopter parenting and their connections to these behaviors. This study aimed to identify profiles of informant discrepancies regarding helicopter parenting within Chinese families and explore their associations with adult children's partner-controlling and partner-controlled behaviors. Matched data from fathers, mothers, and adult children in one hundred and ninety-six intact families were included. Latent profile analysis (LPA) was conducted, identifying four profiles: parents over child (13.78%), child moderately over mother and moderately under father (17.35%), no consistent disagreements (49.49%), and child over parents (19.39%). Children whose perceptions aligned with their parents reported fewer partner-controlling and partner-controlled behaviors, compared to those whose perceptions exceeded their parents'. Similarly, children whose perceptions were lower than their parents' also reported fewer partner-controlled behaviors compared to those with higher perceptions. The findings provide evidence for understanding dynamic patterns of informant discrepancies regarding helicopter parenting in Chinese families and support the development of family-based interventions to address partner-controlling and partner-controlled behaviors.

Simplified shielded MEG-MRI multimodal system with scalar-mode optically pumped magnetometers as MEG sensors

Magnetoencephalography (MEG) conventionally operates within high-performance magnetic shields due to the extremely weak magnetic field signals from the measured objects and the narrow dynamic range of the magnetic sensors employed for detection. This limitation results in elevated equipment costs and restricted usage. Additionally, the information obtained from MEG is functional images, and to analyze from which part of the brain the signals are coming, it is necessary to capture morphological images separately. When MEG and morphological imaging devices are separate, despite their individual high measurement accuracies, discrepancies in positional information may arise. In response, we have developed a low-field magnetic resonance imaging system that incorporates scalar-mode optically pumped magnetometers with a wide dynamic range and exceptionally high measurement sensitivity as sensors for MEG. Operating at low magnetic fields eliminates the need for superconducting coils in magnetic resonance imaging and the high-performance magnetic shields essential for MEG, promising a substantial cost reduction compared to traditional approaches. We achieved a noise level of about 16.7pT/Hz1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${16.7}\\,\\hbox {pT/Hz}^{1/2}$$\\end{document} with a single channel magnetometer, and reached a noise level of 367fT/cm/Hz1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${367}\\,\\hbox {fT/cm/Hz}^{1/2}$$\\end{document} with a baseline of 1 cm through differential measurements. We employed this system to conduct sequential OPM-based magnetic field measurements and MRI imaging, successfully demonstrating the compatibility of high OPM sensitivity with clear MRI acquisition.

MSCMNet: Multi-scale Semantic Correlation Mining for Visible-Infrared Person Re-Identification

The main challenge in the Visible-Infrared Person Re-Identification (VI-ReID) task lies in extracting discriminative features from different modalities for matching purposes. While existing studies primarily focus on reducing modal discrepancies, the modality information fails to be thoroughly exploited. To solve this problem, the Multi-scale Semantic Correlation Mining network (MSCMNet) is proposed to comprehensively exploit semantic features at multiple scales. The network fuses shallow-level features into the deep network through dimensionality reduction and mapping, and the fused features are utilized to minimize modality information loss in feature extraction. Firstly, considering the effective utilization of modality information, the Multi-scale Information Correlation Mining Block (MIMB) is designed to fuse features at different scales and explore the semantic correlation of fusion features. Secondly, in order to enrich the semantic information that MIMB can utilize, the Quadruple-stream Feature Extractor (QFE) with non-shared parameters is specifically designed to extract information from different dimensions of the dataset. Finally, the Quadruple Center Triplet Loss (QCT) is further proposed to address the information discrepancy in the comprehensive features. Extensive experiments on the SYSU-MM01, RegDB, and LLCM datasets demonstrate that the proposed MSCMNet achieves the greatest accuracy. We release the source code on https://github.com/Hua-XC/MSCMNet.

Clinician-caregiver informant discrepancy is associated with sex, diagnosis age, and intervention use among autistic children.

In some cases, a clinician's perceptions of a child's autism-related behaviors are not the same as the child's caregiver's perceptions. Identifying how these discrepancies relate to the characteristics of the child is critical for ensuring that diagnosis procedures are unbiased and suitable for all children. This study examined whether discrepancies between clinician and caregiver reports of autism features related to the child's sex at birth. We also explored how the discrepancies related to the age at which the child received their autism diagnosis and how much intervention they received. We found that clinicians rated autism features higher than caregivers for boys and rated autism features lower than caregivers for girls. In addition, lower clinician relative to parent ratings was related to being diagnosed at an older age and receiving less intervention. These findings suggest that there is more to learn about the presentation of autism-related behaviors in girls. When caregiver and clinician ratings of autism features do not align, it may be important to consider caregivers' ratings to obtain a more accurate picture of the child's autism features and the support they may need.

Overcoming learning bias via Prototypical Feature Compensation for source-free domain adaptation

The focus of Source-free Unsupervised Domain Adaptation (SFUDA) is to effectively transfer a well-trained model from the source domain to an unlabelled target domain. During the target domain adaptation, the source domain data is no longer accessible. Prevalent methodologies attempt to synchronize the data distributions between the source and target domains, utilizing pseudo-labels to impart categorical information, which has made some progress in improving the model’s performance. However, performance impairments persist due to the introduction of learning bias from the source model and the impact of noisy pseudo-labels generated for the target domain. In this research, we reveal that the central cause for feature misalignment during domain transition is the learning bias, which is generated by the discrepancy of information between source and target domain data. The source domain data may contain distinguishable features that do not appear on the target domain, which causes the pre-trained source model to fail to work during domain adaptation. To overcome the information discrepancy, we propose a Prototypical Feature Compensation (PFC) Network. The network extracts representative feature maps of the source domain. Then use them to minimize the discrepancy information in the target domain feature maps. This mechanism facilitates feature alignment across different domains, allowing the model to generate more accurate categorical data through pseudo-labelling. The experimental results and ablation studies demonstrate exceptional performance on three SFUDA datasets and provide evidence of the proposed PFC method’s ability to adjust the feature distribution of both source and target domain data, ensuring their overlap in the latent space.

Socio-demographic variations in prostate cancer diagnosis recording: Primary care compared to the Cancer Registry in England

IntroductionIn the UK, primary care data are often used for cancer-related research, but the accuracy of cancer information is uncertain. ObjectiveWe investigated socio-demographic variation based on the recording date of prostate cancer diagnosis between primary care and the National Cancer Registry (CR). ApproachWe utilised a data extract of 1,600,000 patients over 65 years from Clinical Practice Research Datalink (CPRD). We extracted prostate cancer diagnoses using Read and SNOMED-CT codes from primary care, and ICD-10 from CR. Initial code entry determined diagnosis dates. We categorised recording timing differences as earlier, same-day or later in primary care than CR and used the chi-squared test and logistic regression (adjusted for recording year) to compare these discrepancies across age, deprivation, and ethnicity. ResultsWe included 26,875 men with prostate cancer diagnoses commonly recorded in both sources during 2000-2016 (1,030 excluded with missing ethnicity). Compared to CR, 1,747 (7%) had diagnoses recorded on the same day in primary care, while 20,615 (77%) had later recordings with a median delay of 21 days (IQR: 13-38). Age at diagnosis was associated with recording discrepancies (p<0.001); older men were more likely to have earlier/same-day recordings. Adjusted ORs for age groups were 1.4 (95%CI: 1.3-1.5) for 60-69, 1.3 (1.2-1.5) for 70-79, and 0.9 (0.8-1.0) for ≥80 compared to <60. No associations were found between deprivation (p=0.096) or ethnicity (p=0.067) and recording differences. Conclusion/ ImplicationsThe discrepancy in prostate cancer information between primary care and CR underscores potential biases in studies relying solely on one data source.

A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy.

Federated learning (FL) facilitates the collaborative optimization of fault diagnosis models across multiple clients. However, the performance of the global model in the federated center is contingent upon the effectiveness of the local models. Low-quality local models participating in the federation can result in negative transfer within the FL framework. Traditional regularization-based FL methods can partially mitigate the performance disparity between local models. Nevertheless, they do not adequately address the inconsistency in model optimization directions caused by variations in fault information distribution under different working conditions, thereby diminishing the applicability of the global model. This paper proposes a federated adversarial fault diagnosis method driven by fault information discrepancy (FedAdv_ID) to address the challenge of constructing an optimal global model under multiple working conditions. A consistency evaluation metric is introduced to quantify the discrepancy between local and global average fault information, guiding the federated adversarial training mechanism between clients and the federated center to minimize feature discrepancy across clients. In addition, an optimal aggregation strategy is developed based on the information discrepancies among different clients, which adaptively learns the aggregation weights and model parameters needed to reduce global feature discrepancy, ultimately yielding an optimal global model. Experiments conducted on benchmark and real-world motor-bearing datasets demonstrate that FedAdv_ID achieves a fault diagnosis accuracy of 93.09% under various motor operating conditions, outperforming model regularization-based FL methods by 17.89%.

Evaluative analysis of collection, storage, and transmission of statistical data on tuberculosis at district and central levels of health care in the Republic of Tajikistan

Aim. To assess the effectiveness of collection, storage and transfer of statistical information on tuberculosis in the districts of Rasht region.Material and methods. The material for the planned study was data on registered cases of tuberculosis for 2022 according to the National Tuberculosis Register “OpenMRS”, the Unified Health Management Information Network “DHIS2” and the initial data of primary documentation of the anti-tuberculosis service in five districts of the Rasht region (Rasht, Tajikabad, Sangvor, Nurabad, Lakhsh).Results. The studies conducted revealed a significant discrepancy in the official statistical information on tuberculosis in the unified health management information system “DHIS2”, in the national tuberculosis data register “OpenMRS” and in the primary documentation of the anti-tuberculosis service: Form No. 036, Reporting Form 8, Patient Registration Journal - TB-03 and TB-03U, Quarterly Report Form - TB-07 and TB-07U in all five districts of Rasht region.Conclusion. Frequent criticism of the specialists responsible for providing official statistics on tuberculosis for their inconsistency with WHO data, data from the unified health management information system “DHIS2”, data from the national registry “OpenMRS” and data from the primary documentation of the anti-tuberculosis service is justified. One of the ways to bring official statistical data into line with the real epidemiological situation of tuberculosis is to carry out systematic routine monitoring and evaluation of the quality of collection, storage and transmission of statistical information on tuberculosis from the district level to the central level, to organise continuous training of specialists responsible for this component, to minimise paperwork and to prioritise the digitalisation of this process.

Research on Division of Labor Decision and System Stability of Swarm Robots Based on Mutual Information.

In rational decision-making processes, the information interaction among individual robots is a critical factor influencing system stability. We establish a game-theoretic model based on mutual information to address division of labor decision-making and stability issues arising from differential information interaction among swarm robots. Firstly, a mutual information model is employed to measure the information interaction among robots and analyze its influence on the behavior of individual robots. Secondly, employing the Cournot model and the Stackelberg model, we model the diverse decision-making behaviors of swarm robots influenced by discrepancies in mutual information. The intricate decision dynamics exhibited by the system under the disparity mutual information values during the game process, along with the stability of Nash equilibrium points, are analyzed. Finally, dynamic complexity simulations of the game models are simulated under the disparity mutual information values: (1) When ν1 of the game model varies within a certain range, the Nash equilibrium point loses stability and enters a chaotic state. (2) As I(X;Y) increases, the decision-making pattern of robots transitions gradually from the Cournot game to the Stackelberg game. Concurrently, the sensitivity of swarm robotics systems to changes in decision parameter decreases, reducing the likelihood of the system entering a chaotic state.

Sex Differences and Parent-Teacher Discrepancies in Reports of Autism Traits: Evidence for Camouflaging in a School Setting.

The purpose of this study was to examine sex differences and informant discrepancies in parent- and teacher-reports of autism traits. Data were drawn from the Simons Simplex Collection to create a sex-matched sample of autistic youth (N = 388; 4-17years). Included participants had both parent and teacher reports of autistic traits from the Social Responsiveness Scale (SRS). Within each sex group, parent and teacher raw SRS scores were compared. Scores within each informant group (parent/teacher) was assessed for sex differences. Predictors of parent-teacher discrepancies were examined. Despite no sex differences in parent-reported autistic traits, teachers reported males as having more autistic traits compared to females. Parents of females reported significantly more autistic traits than teachers across multiple domains. Being older and female were significant predictors of increased parent-teacher discrepancy for multiple domains. These results suggest discrepancies between the observed autistic traits for females at home and school and builds on the growing body of literature highlighting potential camouflaging across development in autistic youth: parent-teacher discrepancies may reflect ways that autistic females are overlooked by teachers due to conscious changes in behavior or gender-based expectations of female characteristics. Discussion of discrepancies on an individual basis may therefore alleviate potential long-term consequences of camouflaging.

Attachment Problems and Mentalizing Capacity Relate to Parent-Child Informant Discrepancies in Female Adolescents with Borderline Personality Disorder.

Parent-child informant discrepancies on psychopathology provide important knowledge on the parent-child relationship and the child's mental health, but mechanisms underlying parent-child informant discrepancies are largely unknown. Therefore, we investigated the relationship between attachment problems and mentalizing capacity and parent-child informant discrepancies on borderline personality disorder (BPD) severity, internalizing, and externalizing pathology in a clinical sample of 91 adolescent girls with BPD and their parents. Results showed that more attachment problems to parents and peers were related to adolescents reporting more severe BPD than parents. Adolescents who described more internalizing symptoms relative to parents, reported more parental attachment problems, but enhanced peer attachment, suggesting those adolescents who do not feel recognized by their parents might turn to their friends. When parents rated adolescents higher on externalizing behaviors, the adolescent reported more attachment problems to parents and lower mentalizing capacity, indicating that this sub-group of adolescents may reflect less about how their behavior affects others.

Practice‐focused reflections on adaptive behaviour assessment in autism specialist education

AbstractAdaptive behaviour is crucial for well‐being and independence. The Adaptive Behaviour Assessment System (ABAS‐3) is often used to plan individualised support in specialist educational settings, drawing on both teacher and parent informants. In practice, however, little is known about the extent of variation between informants. We examined informant discrepancies in a naturally occurring dataset of 28 ABAS‐3 assessments (21 male, seven female), performed by teachers and by parents post‐admission at an autism specialist school. We found that in real‐life practice, teachers rated the adaptive functioning capabilities of their students significantly more highly than parents across all ABAS‐3 domains, a discrepancy significantly greater than validation studies with this instrument, and interestingly, non‐uniform across domains. The magnitude of this discrepancy was largest in the Conceptual domain, where differences between informants were greater in older children. The skill area most affected was ‘self‐direction’, which includes aspects of executive function. Existing guidance for adaptive functioning assessment in specialist education is extremely limited; while considering potential sources of informant discrepancy, our findings corroborate the need for further guidance on the use and scope of tools like the ABAS‐3 in educational settings. While such discrepancies may confound population‐level data, individually, these skills may be indicative of greater need to support generalisation across contexts, and may indicate the particular skill areas that are most amenable to intervention.

Evaluating the Problem of Fraudulent Participants in Health Care Research: Multimethod Pilot Study.

The shift toward online recruitment methods, accelerated by the COVID-19 pandemic, has brought to the forefront the growing concern of encountering fraudulent participants in health care research. The increasing prevalence of this issue poses a serious threat to the reliability and integrity of research data and subsequent findings. This study aims to explore the experiences of health care researchers (HCRs) who have encountered fraudulent participants while using online recruitment methods and platforms. The primary objective was to gain insights into how researchers detect and mitigate fraudulent behavior in their work and provide prevention recommendations. A multimethod sequential design was used for this pilot study, comprising a quantitative arm involving a web-based survey followed by a qualitative arm featuring semistructured interviews. The qualitative description approach framed the qualitative arm of the study. Sample sizes for the quantitative and qualitative arms were based on pragmatic considerations that in part stemmed from encountering fraudulent participants in a concurrent study. Content analysis was used to analyze open-ended survey questions and interview data. A total of 37 HCRs participated, with 35% (13/37) of them engaging in qualitative interviews. Online platforms such as Facebook, email, Twitter (subsequently rebranded X), and newsletters were the most used methods for recruitment. A total of 84% (31/37) of participants indicated that fraudulent participation occurred in studies that mentioned incentives in their recruitment communications, with 71% (26/37) of HCRs offering physical or electronic gift cards as incentives. Researchers identified several indicators of suspicious behavior, including email surges, discrepancies in contact or personal information, geographical inconsistencies, and suspicious responses to survey questions. HCRs emphasized the need for a comprehensive screening protocol that extends beyond eligibility checks and is seamlessly integrated into the study protocol, grant applications, and research ethics board submissions. This study sheds light on the intricate and pervasive problem of fraudulent participation in health care research using online recruitment methods. The findings underscore the importance of vigilance and proactivity among HCRs in identifying, preventing, and addressing fraudulent behavior. To effectively tackle this challenge, researchers are encouraged to develop a comprehensive prevention strategy and establish a community of practice, facilitating real-time access to solutions and support and the promotion of ethical research practices. This collaborative approach will enable researchers to effectively address the issue of fraudulent participation, ensuring the conduct of high-quality and ethically sound research in the digital age.

Study on the Design of Traditional Cultural Elements of Packaging under the Chinese Design Trend

Purpose: Exploring the specific problems and design approaches of traditional cultural elements guided by Chinese design trends in packaging, aiming to provide valuable references for designers when designing Chinese-style packaging. Procedures: Starting from the background of the development of Chinese Design Trends, summarizing and analyzing the current design issues by combining the Trompenaars Cultural Layers Theory. In addition, case studies will be used to discuss the design approaches of traditional cultural elements through a thing with Chinese characteristics— Dim sum packaging. Results: The existing problems in Chinese packaging, such as homogenization, superficiality, and information discrepancy, are identified from the perspectives of visual dimension, cultural dimension, and rule dimension. At the same time, it reveals how the elements are designed on Chinese dim sum packaging in terms of direct application, refinement, and transformation. Conclusions: To a certain extent, this study fills the existing problems in the current literature regarding the application of traditional cultural elements in Chinese design trends and reveals the intrinsic nature of the problems through induction and analysis. And explore the Chinese packaging under the trend of Chinese design of cultural elements of the way design.

R2DN – Integrating Databases about Natural Disasters

The historical data on disasters serves various purposes, such as managing the risk of future disasters, assessing risk in the insurance sector, and formulating policies to reduce disaster risks, among others. To meet these objectives, there are databases, covering several types of disasters. However, in addition to differences in purposes, scope, access, and coverage, there are variations in the criteria for registering a disaster in the database and the information used for this register. Due to these differences, we have a scenario with discrepancies of information across existing databases. In this study, we propose a repository that combines the main advantages of some global databases, the data needs due to multilateral agreement, and the possibility of integrating regional or specific databases. The proposed Natural Disaster Data Repository (R2DN) contains a data schema and a data mapping process with two of the main global databases (EM-DAT and DesInventar) and S2ID.

Internalizing Problems in Adopted Eastern European Adolescents: The Role of the Informant, Early Adversity and Post-Adoption Processes.

Internationally adopted children who suffered early institutionalization are at risk of a late onset of internalizing problems in adolescence. Both pre-adoption, adversity-related, and post-adoption factors predict variability in internalizing problems in this population. Previous studies have suggested different patterns of parent-adolescent informant discrepancies in adoptive dyads We analyzed internalizing problems among 66 adolescents internationally adopted from Russia to Spanish families using both the parent- and self-report version of the Strengths and Difficulties Questionnaire and comparing them with a low-risk, community group (n = 30). We assessed pre-adoption and post-adoption factors and evaluated cross-informant discrepancies. Internationally adopted adolescents exhibited more internalizing problems by parent-report than community adolescents, but there were no differences by self-report. Adopted youth showed no discrepancies between parent and self-report, whereas community adolescents reported more internalizing symptoms than their parents. Pre-adoption adversity-related factors predicted parent-reported internalizing problems, while post-adoption factors predicted self-reported internalizing problems. Parent-adolescent informant discrepancies in adopted adolescents from Eastern Europe for internalizing symptoms were lower than in community adolescents. Both adversity-related factors and the lived experience of adoption may influence the development of internalizing symptoms in internationally adopted adolescents.

An adaptive distribution-matched recurrent network for wind power prediction using time-series distribution period division

Precise wind power prediction (WPP) can address the issue caused by large-scale wind power grid integration to the power system operation. Most WPP research focus on the randomness and high volatility problem of wind power but ignore the time-series distribution shift (TSDS) problem. To solve the TSDS issue, this study proposes a novel hybrid model that incorporates complementary ensemble empirical mode decomposition (CEEMD), time-series distribution period division (TSDPD) and adaptive distribution-matched GRU (ADMGRU). First, CEEMD is utilized to decompose the nonstationary data into in sub-sequence, reducing complexity and randomness. Second, TSDPD is employed to automatically identify the underlying temporal segments within wind power sequence by maximizing discrepancies in distribution information between two periods, determining the quantity and respective boundaries of periods. Finally, ADMGRU, comprising Pre-train and Boosting-based importance assessment components, learns prediction model accurately by dynamically matching distribution periods. The former component initializes predictive model parameters and the latter learns the importance of each hidden state to assigns corresponding weights to different distributions. Numerous comparative experiments demonstrate the CEEMD-TSDPD-ADMGRU hybrid model surpasses existing popular models. Especially in spring scenario, compared with other four advanced models, the maximum reduction in MAE and RMSE are 54.64 % and 73.33 %, respectively.

Examining profiles of convergence and divergence in reports of parental warmth: Links to adolescent developmental problems.

Parental warmth during the transition from childhood to adolescence is a key protective factor against a host of adolescent problems, including substance use, maladjustment, and diminished well-being. Moreover, adolescents and parents often disagree in their perceptions of parenting quality, and these discrepancies may confer risk for problem outcomes. The current study applies latent profile analysis to a sample of 687 mother-father-6th grade adolescent triads to identify patterns of adolescent-parent convergence and divergence in perceptions of parental warmth. Five profiles were identified, and associations with adolescent positive well-being, substance use, and maladjustment outcomes in 9th grade were assessed. Patterns of divergence in which adolescents had a pronounced negative perception of parental warmth compared to parents, as well as those wherein pronounced divergence was present in only one adolescent-parent dyad, were associated with diminished positive well-being compared to adolescents who had more positive perceptions of warmth than parents. Having more negative perceptions of warmth compared to parents was also associated with elevated risk for alcohol and marijuana initiation, but only when the divergence was pronounced rather than more moderate. These findings add nuance to findings from previous between-family investigations of informant discrepancies, calling for further family-centered methods for investigating multiple perspectives.

Theory of Mind and Social Informant Discrepancy in Autism.

When autistic youth are asked to assess their own social skills, they frequently rate themselves more favorably than their parents rate them. The magnitude of this informant discrepancy has been shown to relate to key clinical outcomes such as treatment response. It has been proposed that this discrepancy arises from difficulties with Theory of Mind. Participants were 167 youth 11 to 17years old; 72% male, and their parents. Youth completed self-report measures of social skills and social cognitive tasks, while their parents completed questionnaires regarding social skills. A repeated-measures ANOVA indicated both non-autistic and autistic youth rated themselves more favorably than their parents rated them across all measures. Zero-order correlations revealed that raw differences between parent- and participant-report were negatively correlated with scores on parent-reported Theory of Mind measures. However, polynomial analysis did not indicate interaction effects between parent- and participant-report on any of the measures used. Polynomial regression revealed that increases in parent-reported social skill predicted larger increases in parent-report Theory of Mind at low levels of parent-reported social skill compared to high levels of parent-reported social skill. Participant-report social skills predicted performance on a behavioral Theory of Mind test in a curvilinear fashion, such that the relationship was positive at low levels of participant-reported social skills, but negative at high levels. This study replicates the finding that raw difference score analyses may result in illusory effects that are not supported when using more contemporary analysis methods, and that more complex and subtle relationships between social insight and perspective-taking exist within autistic youth.