Interest Items Research Articles

An Examination of the Psychometric Properties of the Paraphilic Interests and Disorders Scale

ABSTRACT The Paraphilic Interests and Disorders Scale (PIDS) is a self-report measure of DSM-5-TR paraphilic interests and disorders. This study further examined the psychometric properties of the PIDS. In Study 1, using a sample of 2,292 adults in the U.S., we examined comorbidity between paraphilic interests to explore internal consistency, which showed those who reported an interest in one paraphilic interest were significantly more likely to report another paraphilic interest. Convergent validity was assessed by comparing PIDS to another measure (Paraphilia Scale), which showed support for convergent validity for the PIDS interests, as well as most behavioral items. In Study 2, a sample of 91 undergraduate students completed the PIDS at two time points. There was at least substantial test-retest reliability for the interest items except sexual sadism. These findings provide psychometric support for the PIDS which may serve as a useful tool for population-based data on paraphilic interests and disorders.

Neuro-symbolic recommendation model based on logic query

Recommendation systems assist users in finding items that are relevant to them. However, recommendation is not only an inductive statistics problem using data; it is also a cognitive task of reasoning decisions based on knowledge extracted from information. Hence, a logic system can naturally be incorporated for reasoning in a recommendation task. Although logic-based hard-rule approaches can provide a powerful reasoning ability, they struggle to cope with inconsistent and incomplete knowledge in real-world tasks, especially for complex tasks such as recommendation. To address these issues, we propose a neuro-symbolic recommendation model, which transforms user history interactions into a logic expression and then transforms the recommendation prediction into a query task based on this logic expression. The logic expressions are then computed based on the modular logic operations of the neural network. We also construct an implicit logic encoder to reasonably reduce the complexity of the logic computation. Finally, a user’s interest items can be queried in the vector space based on the computation results. Experiments on three well-known datasets verified that the proposed method outperforms state of the art shallow, deep, session, and reasoning models.

How best to measure connection to a team: team identification, brand attitude/loyalty, consumer lifestyle or interest level?

PurposeThe purpose of this study was to compare four different consumer pathway models based on identity theory, attitude/loyalty theory, lifestyle theory and hierarchy of effects theory, each with associated instruments measuring connection to the team.Design/methodology/approachThe authors did a two-study analysis, first collecting data from people aware of an NFL team (N = 218) and then an MLS team (N = 209) to determine which connection item performed better.FindingsThe authors found that the Consumer Pathway for Sport Fandom based on the hierarchy of effects theory and its associated interest measurement item performed better than the other three frameworks and items. The Interest item shared the most variance with games attended, games intending to attend, games watched via media and games intending to watch via media.Originality/valueThe Consumer Pathway for Sport Fandom represents the entire consumer spectrum from non-aware consumers all the way up to die-hard sports fans. This pathway will allow sport marketers to track their consumers from initial awareness of the product or service all the way through the brand relationship to ultimate loyalty.

Optimizing Patient-Centered Inclusive Care in Oncology: Healthcare Professionals' Knowledge, Attitudes and Practices Caring for LGBTQ2+ Individuals

<h3>Purpose/Objective(s)</h3> Lesbian, gay, bisexual, transgender, queer/questioning, Two-Spirit, plus (LGBTQ2+) individuals experience cancer-related health disparities and inequities. Our objective was to examine healthcare professionals' (HCPs) knowledge, attitudes, practices and education interest when caring for LGBTQ2+ individuals with cancer, and to identify gaps and opportunities to improve care. <h3>Materials/Methods</h3> A 38-item electronic survey was sent to all Gynecologic oncology staff (<i>n</i>=92) within a tertiary care cancer center in Toronto. Items included respondent demographics (<i>n</i>=7), and LGBTQ2+ knowledge (<i>n</i>=7), attitudes (<i>n</i>=15), practice behaviors <i>(n</i>=5) and education interest (n=1). There were 3 open-ended items exploring personal experiences, reservations, and suggestions for improving LGBTQ2+ care. Knowledge and attitude items were anchored on a 5-point Likert scale with additional options for not sure and prefer not to answer. Practice behaviors and education interest items were measured using categorical response options. Descriptive statistics summarized survey responses. Thematic analysis was used to analyze open-ended questions. <h3>Results</h3> 75/92 HCPs completed the survey (82% response rate). Almost all respondents reported comfort (87-96%; strongly agree/agree) treating LGBTQ2+ individuals, most reported a lack of knowledge about LGBTQ2+ health needs (55-73%). Respondents strongly agreed/agreed it was important to know a patient's sexual orientation and gender identity, while less respondents strongly agreed/agreed that they felt comfortable asking patients (sexual orientation 58% vs 41% p=0.023 and gender identity 82% vs 36% p <0.001). Almost all (96% strongly agreed/agreed) were interested in receiving LGBTQ2+ specific education. Two main themes were identified: (i) HCPs experience fear of offending LGBTQ2+ individuals because of their lack of knowledge, and (ii) HCPs desire LGBTQ2+-specific health training, especially in asking a patient's pronouns, sexual orientation, gender identity, and in caring for transgender patients. <h3>Conclusion</h3> Although HCPs report feeling comfortable caring for LGBTQ2+ individuals, most report a lack of knowledge and awareness in caring for this population. We recommend institutions implement cultural competency training for HCPs to improve inclusive patient-centered care.

NTP-Miner: Nonoverlapping Three-Way Sequential Pattern Mining

Nonoverlapping sequential pattern mining is an important type of sequential pattern mining (SPM) with gap constraints, which not only can reveal interesting patterns to users but also can effectively reduce the search space using the Apriori (anti-monotonicity) property. However, the existing algorithms do not focus on attributes of interest to users, meaning that existing methods may discover many frequent patterns that are redundant. To solve this problem, this article proposes a task called nonoverlapping three-way sequential pattern (NTP) mining, where attributes are categorized according to three levels of interest: strong, medium, and weak interest. NTP mining can effectively avoid mining redundant patterns since the NTPs are composed of strong and medium interest items. Moreover, NTPs can avoid serious deviations (the occurrence is significantly different from its pattern) since gap constraints cannot match with strong interest patterns. To mine NTPs, an effective algorithm is put forward, called NTP-Miner, which applies two main steps: support (frequency occurrence) calculation and candidate pattern generation. To calculate the support of an NTP, depth-first and backtracking strategies are adopted, which do not require creating a whole Nettree structure, meaning that many redundant nodes and parent–child relationships do not need to be created. Hence, time and space efficiency is improved. To generate candidate patterns while reducing their number, NTP-Miner employs a pattern join strategy and only mines patterns of strong and medium interest. Experimental results on stock market and protein datasets show that NTP-Miner not only is more efficient than other competitive approaches but can also help users find more valuable patterns. More importantly, NTP mining has achieved better performance than other competitive methods in clustering tasks. Algorithms and data are available at: https://github.com/wuc567/Pattern-Mining/tree/master/NTP-Miner .

A machine learning approach to enable bulk orders of critical spare-parts in the shipping industry

Purpose: The main purpose of this paper is to propose a methodological approach and a decision support tool, based on prescriptive analytics, to enable bulk ordering of spare parts for shipping companies operating fleets of vessels. The developed tool utilises machine learning and operations research algorithms, to forecast and optimize bulk spare parts orders needed to cover planned maintenance requirements on an annual basis and optimize the company’s purchasing decisions.Design/methodology/approach: The proposed approach consists of three discrete methodological steps, each one supported by a decision support tool based on clustering and machine learning algorithms. In the first step, clustering is applied in order to identify high interest items. Next, a forecasting tool is developed for estimating the expected needs of the fleet and to test whether the needed quantity is influenced by the source of purchase. Finally, the selected items are cost-effectively allocated to a group of vendors. The performance of the tool is assessed by running a simulation of a bulk order process on a mixed fleet totaling 75 vessels.Findings: The overall findings and approach are quite promising Indicatively, shifting demand planning focus to critical spares, via clustering, can reduce administrative workload. Furthermore, the proposed forecasting approach results in a Mean Absolute Percentage Error of 10% for specific components, with a potential for further reduction, as data availability increases. Finally, the cost optimizer can prescribe spare part acquisition scenarios that yield a 9% overall cost reduction over the span of two years.Originality/value: By adopting the proposed approach, shipping companies have the potential to produce meaningful results ranging from soft benefits, such as the rationalization of the workload of the purchasing department and its third party collaborators to hard, quantitative benefits, such as reducing the cost of the bulk ordering process, directly affecting a company’s bottom line.

Indicators Recommendation Algorithm based on Information Entropy and FP Growth for Power Report System

For the Indicators recommendation problem of a power report system without user grade but a large amount of browsing records data, a novel algorithm of mining association rules based on information entropy and Fp-growth is proposed. Firstly, though normalizing the browsing frequency, the information entropy is used to determine the weights of items so as to calculate the interesting measurement value for users. Besides, the forgetting function is introduced to reflect the interest transfer. Then, the FP-growth algorithm is improved by dynamically adjusting support and activity. Finally, the browsing records data of the power report system were used as the test dataset for experiments. The results showed that the algorithm can effectively recommend interest items for users, and the recommendation performance is significantly improved compared with other algorithms.

The internal and external validity of the latent vocational interest circumplex: Structure, relationships with self-concepts, and robustness against item-order effects

The vocational interest circumplex implies a pattern of correlations that can be represented by the interest domains' locations on the circumference of a circle. In addition, the circumplex can be extended by placing external covariates into the two-dimensional interest structure. Results that simultaneously support the circumplex as a model for the interest scales' internal structure and for their external relationships with covariates provide a more comprehensive account of the circumplex's validity than isolated analyses of just one kind of validity evidence. In this article, we outline a latent variable framework that makes it possible to simultaneously examine both validity aspects and that enables researchers to study the robustness of such validity evidence across groups. We applied this framework to the eight basic interest scales of the Personal Globe Inventory (PGI; Tracey, 2002) and their relationships with nine measures of domain-specific self-concepts. Participants were randomly assigned to groups in which the interest items were presented in different orders with the goal of eliciting either cross-domain or within-domain comparisons. Our results suggest that the circumplex structure was remarkably similar (although not fully invariant) across conditions and that the relationships between the PGI scales and the self-concept domains were in good agreement with the circumplex regardless of item order. Interestingly, most self-concept scales occupied positions along the People-Things axis of the circumplex, thereby replicating previous results on the relationships of vocational interests and ability-related constructs. Taken together, our results provide strong support for the internal and external validity of the interest circumplex as an integrative map for representing complex construct relationships.

A hybrid recommendation system based on profile expansion technique to alleviate cold start problem

Recommender systems are one of the information filtering tools which can be employed to find interest items of users. Collaborative filtering is one of the recommendation methods to provide suggestions for target users based on the ratings of like-interest users. This method suffers from some shortcomings such as cold start problem leading to reduce the performance of recommender system in predicting unseen items. In this paper, we propose a hybrid recommendation method based on profile expansion technique to alleviate cold start problem in recommender systems. For this purpose, we take into consideration user’s demographic data (e.g. age, gender, and occupation) beside user’s rating data in order to enrich the neighborhood set of users. Specifically, two different strategies are used to enrich the rating profile of users by adding some additional ratings to them. The proposed rating profile expansion mechanism has a significant effect on the performance improvement of recommender systems especially when they are facing with cold start problem. The reason behind this claim is that the proposed mechanism makes a denser user-item rating matrix than the original one by adding some additional ratings to it. Obviously, providing a rating profile with further ratings for the target user leads to alleviate cold start problem in recommender systems. The expanded rating profiles are used to calculate similarity values between users and predict unseen items. The results of experiments demonstrate that the proposed method can achieve better performance than the other recommendation methods in terms of accuracy and rate coverage measures.

MUSIC® for Medical Students: Confirming the Reliability and Validity of a Multi-Factorial Measure of Academic Motivation for Medical Education

Construct: The MUSIC® Inventory measures the construct of academic motivation across five factors: empowerment, usefulness, success, interest, and caring. The factors are defined in terms of the degree the student perceives that they have control over their environment, that the coursework is useful to their future, that they can succeed in the course, that the course and instructional methods are interesting, and that the teacher cares about their wellbeing and their success respectively. Background: A valid measure of medical students’ academic motivation would provide medical teachers with a method for evaluating the motivational aspect of their course and provide focus for changes in teaching and learning to improve medical student engagement. While the MUSIC® Inventory structure has been validated in the tertiary setting and with several professional programs, it has not been validated with medical students. The aim of this study was to use both classical test theory and Rasch modeling to assess the reliability and confirm the structure of the five-factor model of the MUSIC® Inventory with medical students. Approach: One-hundred-fifty-two medical students completed the 26-item inventory. Descriptive statistics, internal consistency, correlations between factors, confirmatory factor analysis, and Rasch analysis using the rating scale model were performed to determine reliability and validity. Findings: The five factors showed good internal consistency (Cronbach’s alpha .87 – .92). Correlations between factors were moderate to high (r = .38 – .89). Confirmatory factor analysis highlighted inconsistencies in factor loadings of three of the items hypothesized to measure interest. Rasch analysis using the rating scale model showed that all items for each factor had good item fit (0.65 – 1.37). Person separation (2.28 – 2.85) and reliability (.84 –.91) scores indicated that the scales were able to differentiate different levels of respondents. Item separation (2.25 – 6.97) and reliability scores (.83 –.98) indicated that the items of the scales were being differentiated by the respondents. Conclusions: Rasch analysis indicates that the five factors of academic motivation measured by the MUSIC® Inventory account for the response patterns in data from medical students. However, while the factors of empowerment, usefulness, success, and caring showed expected reliability and validity using classical analysis, three of the interest items cross-loaded on to the usefulness factor. Possible reasons may include ambiguity of language for the items or medical students’ conception of usefulness and interest. Future research will explore medical students’ understanding of the language used to measure these factors in further detail.

Establishing Canadian metrics for self-report measures used to assess hypersexuality

We examined the prevalence of hypersexuality in two combined Canadian adult community samples totalling 1,857 respondents (female n = 960, male n = 835, other n = 60, missing n = 2). Participants were recruited from social media to complete an online sexual behaviour survey that included two measures of compulsive sexual behaviour disorder— the Sexual Compulsivity Scale (SCS) and Hypersexual Behaviour Inventory (HBI)—as well as sexual behaviour and interest items. Respondents also reported their total sexual outlets (TSO)—defined by number of orgasms experienced weekly—as a third potential indicator of hypersexuality. Canadian men and women reported multiple sexual outlets per week that tended to be higher than previous reports. Men tended to report a larger number and higher frequency of various sexual behaviour than women, including higher rates of compulsive sexual behaviour disorder, which varied depending on the measure employed. Implications for establishing sexuality norms and conceptualizing hypersexuality and compulsive sexual behaviour disorder are discussed.

The structure of the quality of clinical practice guidelines with the items and overall assessment in AGREE II: a regression analysis

BackgroundThe Appraisal of Guidelines for Research & Evaluation (AGREE) II has been widely used to evaluate the quality of clinical practice guidelines (CPGs). While the relationship between the overall assessment of CPGs and scores of six domains were reported in previous studies, the relationship between items constituting these domains and the overall assessment has not been analyzed. This study aims to investigate the relationship between the score of each item and the overall assessment and identify items that could influence the overall assessment.MethodsAll Japanese CPGs developed using the evidence-based medicine method and published from 2011 to 2015 were used. They were independently evaluated by three appraisers using AGREE II. The evaluation results were analyzed using regression analysis to evaluate the influence of 6 domains and 23 items on the overall assessment.ResultsA total of 206 CPGs were obtained. All domains and all items except one were significantly correlated to the overall assessment. Regression analysis revealed that Domain 3 (Rigour of Development), Domain 4 (Clarity of Presentation), Domain 5 (Applicability), and Domain 6 (Editorial Independence) had influence on the overall assessment. Additionally, four items of AGREE II, clear selection of evidence (Item 8), specific/unambiguous recommendations (Item 15), advice/tools for implementing recommendations (Item 19), and conflicts of interest (Item 22), significantly influenced the overall assessment and explained 72.1% of the variance.ConclusionsThese four items may highlight the areas for improvement in developing CPGs.

An efficient hybrid similarity measure based on user interests for recommender systems

AbstractRecommender systems are used to suggest items to users based on their interests. They have been used widely in various domains, including online stores, web advertisements, and social networks. As part of their process, recommender systems use a set of similarity measurements that would assist in finding interesting items. Although many similarity measurements have been proposed in the literature, they have not concentrated on actual user interests. This paper proposes a new efficient hybrid similarity measure for recommender systems based on user interests. This similarity measure is a combination of two novel base similarity measurements: the user interest–user interest similarity measure and the user interest–item similarity measure. This hybrid similarity measure improves the existing work in three aspects. First, it improves the current recommender systems by using actual user interests. Second, it provides a comprehensive evaluation of an efficient solution to the cold start problem. Third, this similarity measure works well even when no corated items exist between two users. Our experiments show that our proposed similarity measure is efficient in terms of accuracy, execution time, and applicability. Specifically, our proposed similarity measure achieves a mean absolute error (MAE) as low as 0.42, with 64% applicability and an execution time as low as 0.03 s, whereas the existing similarity measures from the literature achieve an MAE of 0.88 at their best; these results demonstrate the superiority of our proposed similarity measure in terms of accuracy, as well as having a high applicability percentage and a very short execution time.

Toward a dimensional model of vocational interests.

Growing evidence on the predictive validity of vocational interests for job performance calls for greater consideration of interest assessment in organizations. However, a consensus on the fundamental dimensions of interests that are aligned with the contemporary world of work is still lacking. In the current research, we developed an organizing framework of vocational interests and empirically validated an 8-dimension model (SETPOINT: Health Science, Creative Expression, Technology, People, Organization, Influence, Nature, and Things). We propose that interests are structured hierarchically, with preferences for specific work activities at the lowest level (assessed using interest items), basic interests for homogeneous classes of activities at the intermediate level (assessed using basic interest scales), and broad-band interest dimensions describing general tendencies of individuals to be drawn to or motivated by broad types of work environments at the top. To derive broad-band interest dimensions, it is necessary to base it on a comprehensive range of content-specific basic interest constructs. In Study 1, we conducted an extensive review of existing basic interest scales and developed a new assessment of basic interests with 41 homogeneous scales across two samples. In Study 2, we demonstrated the structural validity of the proposed dimensional model using second-order confirmatory factor analysis and exploratory structural equation modeling with a large, diverse sample of working adults and supported its predictive validity for occupational membership in new and traditional sectors of work. We discuss implications from the current findings for building interest theory, using interest assessment for organizational research, and evaluating interest structure with appropriate methods. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Response latency in interest assessment: An added tool?

In this study, we used reports of and response times to vocational interest assessment from 989 adults on the Personal Globe Inventory-Short (PGI-Short) and Personal Globe Inventory-Mini (PGI-Mini) to examine the associations between item response and response latency and the potential additive effects of response latency on interest assessment. Findings revealed a curvilinear relation between item response and mirrored response latency such that individuals responded to interest items more quickly when they strongly like or dislike an activity and took longer time to respond when their interests were ambivalence. Further, reflected response latency were found to enhance reliability for both the PGI-Short and the PGI-Mini, and the fit between the combined item response and responding latency vocational interests had additional predictive effects on vocational certainty, over and beyond the effects of regular item responses, but only for the PGI-Mini. Applications and implications of item response latency to interest and other assessments were discussed.

PHANTOM SCYTHIANS MOUND NEAR THE SUMY CITY

In 1926 collection of items that allegedly were founded in a mound near the Sumy city of Kharkov province was transferred to the State Hermitage museum from the storehouse of antiquities of the State Academy for the History of Material Culture. According to the information given in the museums inventory book, this mound was excavated by N. E. Makarenko in 1915. However we couldn’t find any documents confirming this research. Even if the mound near the Sumy city existed, details of its structure as well as circumstances of the items discovery are still unknown. The most of peculiar interest items in the Hermitage collection are numerous iron parts of two Scythian-type wagons. In this article we have proposed the reconstruction of the wheels of these wagons that based in the analysis of the items. For some parts of wagons we have found analogies in the Scythian mounds in the Dnieper and the Kuban areas. At the same time, in the Hermitage collection there are Sindo-Meotian type swords and Meotian pottery of the IV century BC. Considering this fact, we have reviewed an alternative version of the origin of wagons parts. Some indirect signs allow us to correlate items from a mound near the Sumy city with the famous Elizabethan burial mounds. This fact is confirmed also by the comparison items from Hermitage collection with archive documents of excavations of the Elizabethan burial ground, in particular, with the photo of the wheels that were founded in the mound, excavated in 1915.

Differences in change blindness to real-life scenes in adults with autism spectrum conditions

People often fail to detect large changes to visual scenes following a brief interruption, an effect known as ‘change blindness’. People with autism spectrum conditions (ASC) have superior attention to detail and better discrimination of targets, and often notice small details that are missed by others. Together these predict people with autism should show enhanced perception of changes in simple change detection paradigms, including reduced change blindness. However, change blindness studies to date have reported mixed results in ASC, which have sometimes included no differences to controls or even enhanced change blindness. Attenuated change blindness has only been reported to date in ASC in children and adolescents, with no study reporting reduced change blindness in adults with ASC. The present study used a change blindness flicker task to investigate the detection of changes in images of everyday life in adults with ASC (n = 22) and controls (n = 22) using a simple change detection task design and full range of original scenes as stimuli. Results showed the adults with ASC had reduced change blindness compared to adult controls for changes to items of marginal interest in scenes, with no group difference for changes to items of central interest. There were no group differences in overall response latencies to correctly detect changes nor in the overall number of missed detections in the experiment. However, the ASC group showed greater missed changes for marginal interest changes of location, showing some evidence of greater change blindness as well. These findings show both reduced change blindness to marginal interest changes in ASC, based on response latencies, as well as greater change blindness to changes of location of marginal interest items, based on detection rates. The findings of reduced change blindness are consistent with clinical reports that people with ASC often notice small changes to less salient items within their environment, and are in-line with theories of enhanced local processing and greater attention to detail in ASC. The findings of lower detection rates for one of the marginal interest conditions may be related to problems in shifting attention or an overly focused attention spotlight.

Reared-Apart Chinese Twins: Chance Discovery/Twin-Based Research: Twin Study of Media Use; Twin Relations Over the Life Span; Breast-Feeding Opposite-Sex Twins/Print and Online Media: Twins in Fashion; Second Twin Pair Born to Tennis Star; Twin Primes; Twin Pandas.

A January 2017 reunion of 10-year-old reared-apart Chinese twin girls was captured live on ABC's morning talk show Good Morning America, and rebroadcast on their evening news program Nightline. The twins' similarities and differences, and their participation in ongoing research will be described. This story is followed by reviews of twin research concerning genetic and environmental influences on media use, twin relations across the lifespan and the breast-feeding of opposite-sex twins. Popular interest items include twins in fashion, the second twin pair born to an internationally renowned tennis star, twin primes and twin pandas.

Exploring vocational and academic fields of study: development and validation of the Flemish SIMON Interest Inventory (SIMON-I)

A new, Holland-based Interest Inventory is proposed, intended to facilitate the transition from secondary to tertiary education. Specific interest items were designed to grasp activities that are prevalent during tertiary studies, including an Academic-track-scale to assist in the choice between academic and vocational-oriented programs. Interest profile descriptions are complemented by a list of matching study programs. Data from 3,962 students were analyzed to evaluate the underlying circumplex structure, the criterion validity of the Academic-track-scale and the study program RIASEC codes. It is concluded that the assessment and feedback tools are promising instruments to facilitate the transition to tertiary education.

Interests shape how adolescents pay attention: the interaction of motivation and top-down attentional processes in biasing sensory activations to anticipated events.

The voluntary allocation of attention to environmental inputs is a crucial mechanism of healthy cognitive functioning, and is probably influenced by an observer's level of interest in a stimulus. For example, an individual who is passionate about soccer but bored by botany will obviously be more attentive at a soccer match than an orchid show. The influence of monetary rewards on attention has been examined, but the impact of more common motivating factors (i.e. the level of interest in the materials under observation) remains unclear, especially during development. Here, stimulus sets were designed based on survey measures of the level of interest of adolescent participants in several item classes. High-density electroencephalography was recorded during a cued spatial attention task in which stimuli of high or low interest were presented in separate blocks. The motivational impact on performance of a spatial attention task was assessed, along with event-related potential measures of anticipatory top-down attention. As predicted, performance was improved for the spatial target detection of high interest items. Further, the impact of motivation was observed in parieto-occipital processes associated with anticipatory top-down spatial attention. The anticipatory activity over these regions was also increased for high vs. low interest stimuli, irrespective of the direction of spatial attention. The results also showed stronger anticipatory attentional and motivational modulations over the right vs. left parieto-occipital cortex. These data suggest that motivation enhances top-down attentional processes, and can independently shape activations in sensory regions in anticipation of events. They also suggest that attentional functions across hemispheres may not fully mature until late adolescence.