Real-world Interactions Research Articles

End of libraries/renaissance in the “peer-to-peer sharing economy” revolution age? Librarians of the future educating for a sustainable world

PurposeLibraries face an uncertain situation in present times of the “digital revolution” while every single sector moved online. The purpose of this paper is to search and propose potential library actions as response to the challenge of the peer-to-peer (p2p) sharing platform revolution in business models, a revolution to gain efficiency and to protect the environment.Design/methodology/approachThis research focused on integrating economics and library concepts based on a selective literature review and real-world interaction. The main concern is to connect library possibilities with the emergence of p2p digital platforms, which has enabled individuals to make use of underused inventory via fee-based sharing, as a way of obtaining, giving or sharing access to goods and services. The authors balance the existing proposals to achieve how librarians can help.FindingsThis paper defines key types of potential applications for platform business models in the sharing economy promoted by librarians and describes their characteristics for the renaissance of the “New libraries”. First, “educating” society to face critically the disruptive change in networks of culture and information. Second, “growing” as key reference institutions and community service centres integrating “external” skills. Third, “promoting” the disruptive economy by creation or participation in digital platforms. Fourth, “creating” cooperative markets through social-economic currencies.Originality/valueThis research was carried out with the objective of determining how librarians contribute to sustainable development. All four proposals to implement represent possibilities that derive from the sharing economy approach at different levels of implementation according to the degree of commitment that librarians require to translate into specific actions.

Quo Vadis Psychiatry? Why It Is Time to Endorse Evolutionary Theory.

In recent decades, psychiatry and the neurosciences have made little progress in terms of preventing, diagnosing, classifying, or treating mental disorders. Here we argue that the dilemma of psychiatry and the neurosciences is, in part, based on fundamental misconceptions about the human mind, including misdirected nature-nurture debates, the lack of definitional concepts of "normalcy," distinguishing defense from defect, disregarding life history theory, evolutionarily uninformed genetic and epigenetic research, the "disconnection" of the brain from the rest of the body, and lack of attention to actual behavior in real-world interactions. All these conceptual difficulties could potentially benefit from an approach that uses evolutionary theory to improve the understanding of causal mechanisms, gene-environment interaction, individual differences in behavioral ecology, interaction between the gut (and other organs) and the brain, as well as cross-cultural and across-species comparison. To foster this development would require reform of the curricula of medical schools.

Peer contagion dynamics in the friendships of children with ADHD.

Friendships in middle childhood carry high developmental significance. The majority of children with attention-deficit/hyperactivity disorder (ADHD) have few friendships, unstable friendships, or poor relationship quality in any friendships they have. The current study used time-window sequential analysis to map the dynamics within the friendships of children with ADHD, specifically the peer contagion processes of dyadic mutuality and coercive joining. Participants were 164 dyads consisting of a target child with ADHD and peer problems (age 6-11years; 68% male; and 73% white) and a reciprocated friend. Dyads were observed in the lab during a cooperative task eliciting verbal negotiation processes to decide how to share a limited resource and during a fast-paced, engrossing, and competitive task. Both tasks were designed to mirror the real-world interactions of friends. Sequences of dyadic mutuality (i.e., reciprocity of positive affect and positive behaviors) and coercive joining (i.e., reciprocity of aggressive, controlling, and rule-breaking behaviors) between target children and friends were coded. Regarding dyadic mutuality, target children reciprocated their friends' positive affect in both tasks. They also reciprocated their friends' positive behaviors but only in the cooperative task. In contrast, they only reciprocated their friends' coercive joining behaviors in the competitive task. Medium to large reciprocity effects was found for 36%-53% (dyadic mutuality) and 38%-55% (coercive joining) of target children. These results extend findings of peer contagion processes to the friendships of children with ADHD and suggest that contagion may vary according to interaction context (i.e., competition vs. cooperation). Understanding the spread of peer contagion may illuminate how children with ADHD and their friends influence each other's adjustment over time and may guide friendship-focused psychosocial interventions for this population.

Robots in Eldercare: How Does a Real-World Interaction with the Machine Influence the Perceptions of Older People?

(1) Background: Using autonomous social robots in selected areas of care for community-dwelling older adults is one of the promising approaches to address the problem of the widening care gap. We posed the question of whether a possibility to interact with the technology to be used had an impact on the scores given by the respondents in various domains of needs and requirements for social robots to be deployed in care for older individuals. (2) Methods: During the study, the opinions of older people (65+; n = 113; with no severe cognitive impairment) living in six social care institutions about a robot in care for older people were collected twice using the Users’ Needs, Requirements and Abilities Questionnaire (UNRAQ): after seeing a photo of the robot only and after a 90–150 min interaction with the TIAGo robot. (3) Results: Mean total scores for both assistive and social functions were higher after the interaction (p < 0.05). A positive correlation was found between opinion changes in social and assistive functions (r = 0.4842; p = 0.0000). (4) Conclusions: Preimplementation studies and assessments should include the possibility to interact with the robot to provide its future users with a clear idea of the technology and facilitate necessary customisations of the machine.

Distinct Effects of Antidepressants in Association With Mood Stabilizers and/or Antipsychotics in Unipolar and Bipolar Depression.

There is a dearth of studies comparing the clinical outcomes of patients with treatment-resistant unipolar (TRD) depression and depression in bipolar disorder (BD) despite similar treatment strategies. We aimed to evaluate the effects of the pharmacological combinations (antidepressants [AD], mood stabilizers [MS], and/or antipsychotics [AP]) used for TRD and BD at the McGill University Health Center. We reviewed health records of 206 patients (76 TRD 130 BD) with TRD and BD treated with similar augmentation strategies including AD with MS (AD+MS) or AP (AD+AP) or combination (AD+AP+MS). Clinical outcomes were determined by comparing changes on the 17-time Hamilton Depression Rating Scale (HAMD-17), Quick Inventory of Depressive Symptomatology, and Clinical Global Impression-Severity of Illness at the beginning (T0) and after 3 months of an unchanged treatment (T3). Baseline HAMD-17 scores in TRD were higher than in BD (P < 0.001), but TRD patients had a greater improvement at end point (P = 0.003). Antidepressants with AP generated greater reductions in HAMD-17 in TRD compared with BD (P = 0.02). Importantly, in BD patients, the addition of AD compared with other treatment strategies failed to improve the outcome. The limitations of this study include possibly unrepresentative subjects from tertiary care settings, incomplete matching of BD and TRD subjects, nonrandomized treatment with unmatched agents, doses, and times, unknown treatment adherence, and nonblinded retrospective outcome assessments. Nevertheless, the findings may reflect real-world interactions of clinically selected pharmacotherapies. Combination of augmentation strategies such as AD+AP and/or MS showed a better clinical improvement in patients with TRD compared with BD suggesting a limited evidence for AD potentiation in BD.

Assessing and Optimizing Socio-Moral Reasoning Skills: Findings From the MorALERT Serious Video Game

BackgroundSocial cognition and competence are a key part of daily interactions and essential for satisfying relationships and well-being. Pediatric neurological and psychological conditions can affect social cognition and require assessment and remediation of social skills. To adequately approximate the complex and dynamic nature of real-world social interactions, innovative tools are needed. The aim of this study was to document the performance of adolescents on two versions of a serious video game presenting realistic, everyday, socio-moral conflicts, and to explore whether their performance is associated with empathy or sense of presence, factors known to influence social cognition.MethodsParticipants (12–17 years, M = 14.39; SD = 1.35) first completed a pre-test measure of socio-moral reasoning based on three dilemmas from a previously validated computer task. Then, they either played an evaluative version (n = 24) or an adaptive (n = 33) version of a video game presenting nine social situations in which they made socio-moral decisions and provided justifications. In the evaluative version, participants’ audio justifications were recorded verbatim and coded manually to obtain a socio-moral reasoning maturity score. In the adaptive version (AV), tailored feedback and social reinforcements were provided based on participant responses. An automatic coding algorithm developed using artificial intelligence was used to determine socio-moral maturity level in real-time and to provide a basis for the feedback and reinforcements in the game. All participants then completed a three-dilemma post-test assessment.ResultsThose who played the adaptive version showed improved SMR across the pre-test, in-game and post-test moral maturity scores, F(1.97,63.00) = 9.81, pHF < 0.001, ϵ2 = 0.21, but those who played the Evaluative version did not. Socio-moral reasoning scores from both versions combined did not correlate with empathy or sense of presence during the game, though results neared significance. The study findings support preliminary validation of the game as a promising method for assessing and remediating social skills during adolescence.

Personalizing interventions using real-world interactions: Improving symptoms and social functioning in schizophrenia with tailored metacognitive therapy.

When clients' lives are not reflected in therapy, they struggle to apply the skills learned in treatment to everyday situations. In this pilot study, we determined if using clients' real-world interactions in therapy could effectively target metacognitive capacity-yielding improved symptoms and social functioning-by tailoring treatment to focus on issues faced by clients in daily life. Using a randomized controlled trial design, schizophrenia subjects with metacognitive deficits completed 24 sessions of: (a) Standard Metacognitive Reflection and Insight Therapy (MERIT); or (b) Tailored MERIT. Real-world interactions were captured via the Electronically Activated Recorder (EAR), a smartphone application that passively records audio in daily life. All subjects wore the EAR; however, real-world interactions were only used to personalize sessions in Tailored MERIT. Feasibility and acceptability were shown; those in Tailored MERIT wore the EAR 84% of their waking hours and reported minimal burden. When compared to Standard MERIT, Tailored MERIT participants showed large pre-post reductions in negative metacognitive beliefs and disorganized symptoms. Small, but nonsignificant, improvements in social functioning were also observed. Compared to an evidence-based benchmark, we observed that real-world interactions can be used to tailor metacognitive therapy and improve outcomes in schizophrenia. Tailored MERIT has the potential to impact practice by personalizing treatment to account for individual variations in environment and lifestyle-aligning with the Precision Medicine Initiative-in a way that is not possible with current therapy. This is particularly salient in schizophrenia, where limited insight and cognitive deficits often make subjective reporting unreliable. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

“Are we tweeting our real selves?” personality prediction of Indian Twitter users using deep learning ensemble model

Social Networking Sites have significant potential to reveal valuable explicit as well as implicit statistics and patterns when deep learning is applied to their raw and unstructured data. Tweets posted by the users on their timeline not only reflect their mindset, their likes and dislikes but could also be used to unveil significant amount of information about many psychological aspects and behavior that may be hard to study directly. This paper aims to predict the personality of the 100 real-time Twitter users conforming to personality traits in the BIG 5 model by extracting features from their tweets using ensemble of CNN (Convolutional Neural Network) and BiLSTM (Bidirectional Long Short Memory). The findings of our experiment shows that our model performs slightly better than previous baselines methods achieving an accuracy 75.134% on testing data. We have further hypothesized that unrestricted data available on Twitter may contain features that can be used to predict the personality of its user. It was concluded that personality of Twitter users in the real world is reflected in their online behaviour, reinforcing the premise that the nature of online interactions does not significantly differ from that of real-world interactions. Overall, the study provides a deep insight into the impact of social media data in providing predictive indicators of user behavior.

High-Resolution Eye-Tracking during Natural Real-World Interaction

High-Resolution Eye-Tracking during Natural Real-World Interaction

Greater Social Interest Between Autistic and Non-autistic Conversation Partners Following Autism Acceptance Training for Non-autistic People.

Bi-directional differences in social communication and behavior can contribute to poor interactions between autistic and non-autistic (NA) people, which in turn may reduce social opportunities for autistic adults and contribute to poor outcomes. Historically, interventions to improve social interaction in autism have focused on altering the behaviors of autistic people and have ignored the role of NA people. Recent efforts to improve autism understanding among NA adults via training have resulted in more favorable views toward autistic people, yet it remains unknown whether these benefits extend to real-world interactions between autistic and NA people. The current study explores whether a brief autism acceptance training (AAT) program can improve social interactions between autistic and NA adults. Thirty-nine NA males were randomly assigned to complete AAT or a no-training control condition, then participated in a 5-min unstructured conversation with an unfamiliar autistic male (n = 39). Following the conversation, participants rated their perceptions of interaction quality, first impressions of their partner, and their interest in future interactions with their partner. In dyads where the NA individual completed AAT, both the autistic and NA person endorsed greater future interest in hanging out with their partner relative to dyads in which the NA adult did not complete AAT. However, other social interaction outcomes, including ratings of interaction quality and first impressions of autistic partners, largely did not differ between training and no-training conditions, and assessments of the interaction were largely unrelated for autistic and NA partners within dyads. Results also indicated that NA participants, but not autistic participants, demonstrated substantial correspondence between evaluations of their partner and the interaction, suggesting that autistic adults may place less weight on trait judgments when assessing the quality of an interaction. These findings suggest that the brief AAT for NA adults used in this study may increase mutual social interest in real-world interactions between NA and autistic adults, but more systematic changes are likely needed to bridge divides between these individuals. Future work with larger, more diverse samples is recommended to further explore whether interventions targeting NA adults are beneficial for improving autistic experiences within NA social environments.

Characterizing the Interpersonal Neural Dynamics of Real-World Social Interactions: Evidence From Classrooms and Museums

Characterizing the Interpersonal Neural Dynamics of Real-World Social Interactions: Evidence From Classrooms and Museums

Supplemental Material for Personalizing Interventions Using Real-World Interactions: Improving Symptoms and Social Functioning in Schizophrenia With Tailored Metacognitive Therapy

Supplemental Material for Personalizing Interventions Using Real-World Interactions: Improving Symptoms and Social Functioning in Schizophrenia With Tailored Metacognitive Therapy

Trust Miscalibration Is Sometimes Necessary: An Empirical Study and a Computational Model

The literature on trust seems to have reached a consensus that appropriately calibrated trust in humans or machines is highly desirable; miscalibrated (i.e., over- or under-) trust has been thought to only have negative consequences (i.e., over-reliance or under-utilization). While not invalidating the general idea of trust calibration, a published computational cognitive model of trust in strategic interaction predicts that some local and temporary violations of the trust calibration principle are critical for sustained success in strategic situations characterized by interdependence and uncertainty (e.g., trust game, prisoner’s dilemma, and Hawk-dove). This paper presents empirical and computational modeling work aimed at testing the predictions of under- and over-trust in an extension of the trust game, the multi-arm trust game, that captures some important characteristics of real-world interpersonal and human-machine interactions, such as the ability to choose when and with whom to interact among multiple agents. As predicted by our previous model, we found that, under conditions of increased trust necessity, participants actively reconstructed their trust-investment portfolios by discounting their trust in their previously trusted counterparts and attempting to develop trust with the counterparts that they previously distrusted. We argue that studying these exceptions of the principle of trust calibration might be critical for understanding long-term trust calibration in dynamic environments.

Sustaining Dialogue in Polarised Political Contexts

The rise of populism is a prevalent issue on the political landscape both in Europe and the wider world. Such ideologies create defamatory political narratives and exacerbate already partisan social media spaces. This trend challenges psychologists interested in politics to consider what factors could influence dialogue sustainment in these polarised contexts. The current focus of social psychology research is towards identity-based theories to mediate such interactions. The purpose of this paper is to challenge the idea that identity-models are the only effective means of depolarising real-world, discursive political conflicts. This article critiques identity on the following: (1) Ontological assumptions of binary group oppositionality are limiting and unrepresentative of real-world interactions, and (2) Current identity-based models for mediating are ineffective in highly polarised, real-world contexts. We consider the issue of polarising political discourse from a dialogical perspective and propose the Dialogue Sustainment Theoretical Model as an alternative. The model considers: (1) Citizens as political actors with worldviews, (2) The role of the dynamic &amp; relational positionality, and (3) The influence of chronotopic boundaries on political debate. Whilst we acknowledge identity can transcend polarisation in certain contexts, it does not possess such a capacity in politically polarised, real-world contexts. Instead, we argue for an alternative model which is dialogically-focused and offers a distinctive insight into sustaining dialogue.

Self–other moral bias: Evidence from implicit measures and the Word-Embedding Association Test

Self–other bias can engender disagreement, misunderstanding, and conflict in real-world interactions. Moral perspectives are powerful in shaping thoughts and behaviors. Whether there is a self–other moral bias is poorly understood. We leveraged the Implicit Association Test (Study 1), the evaluative priming task (Study 2), and the Word-Embedding Association Test (Study 3) to demonstrate the self–other moral bias. We found that 1) people held a significantly stronger association between self and deontology (other and utilitarianism) than other and deontology (self and utilitarianism); and 2) the association between the self and other words and the deontological and utilitarian words was further identified in large bodies of English-language text from the Internet. An awareness of the self–other moral bias may facilitate a better understanding of others' attitudes and behaviors.

Designing Pedagogically Effective Haptic Systems for Learning: A Review

Haptic technology enables users to utilize their sense of touch while engaging with a virtual representation of objects in a simulated environment. It is a bidirectional technology in that it facilitates the interaction between the user and these virtual representations by allowing them to apply force onto one another, which is analogous to our real-world interactions with physical objects as action-reaction pairs. The sense of touch is a powerful and innate learning tool that we readily employ starting from very early ages as infants even before learning to walk. Therefore, it is natural that incorporating haptic technology into pedagogical methods has been an active research area as it has significant potential to enrich the learning experience and provide an engaging environment for learners. In this paper, we reviewed studies from various disciplines that incorporate haptics to increase the quality of teaching and learning while emphasizing the underlying cognitive theories. In that direction, we describe two of the most common cognitive theories, the Cognitive Load and Embodied Cognition theories, that developers use to support haptic technology’s implications and use in learning environments. We then explore the effects of haptic design on its current applicability following these two theories. Finally, we summarize the best design practices to develop haptic simulations for learning, address gaps in current research, and propose new research directions.

Uncovering conceptual metaphors in Donald Trump’s Twitter before and after the COVID-19 outbreak

Global leaders have addressed the COVID-19 pandemic in various ways and registers well beyond the scientific-technical genre, some of which have been unexpectedly undermined by a war-like undertone broadcast by both the media and social networks (cf. conceptual metaphor as discussed, for example, by Lakoff, &amp; Johnson 1980, and Koller 2011). According to Hartmann-Mahmud (2002), metaphors are often exploited to manipulate emotion and to justify courses of action related, in this case, to a pandemic scenario, thereby potentially fostering the labelling of the virus with lexemes such as an enemy, invisible or hidden, or even as a prompter for war, hatred, prejudice and racism. Particularly interesting for this research paper is the study in progress of the occurrence of metaphors, associated with the pandemic, retrieved from the Twitter of Donald Trump (https://twitter.com/realDonaldTrump), especially given his reported high engagement with interlocutors in social media (Walther 1992, Crystal 2006, Greengard 2009, Murthy 2013, Baym 2015, Burgess, &amp; Baym 2020). The corpora comprise all original tweets disseminated by Trump in two periods: the first from September 2019 to January 2020; and the latter from February to June 2020. Drawing on corpus linguistics and a discourse-based approach (Baker 2006), it is possible to account for metaphors associated with the lemma COVID in Trump’s Twitter. Research findings indicate 123 occurrences of the lemma virus closely associated with the following lexical items: corona, Covid, China, Chinese, hidden enemy, invisible enemy and war. This study analyses conceptual metaphors in Trump’s communicative strategies throughout the early and mid-stages of the pandemic. Hence, it reflects upon the impact of figurative language in the social construction of meaning, particularly that of leaders’ interactions with citizens and internet followers in real world interactions via social media, which borrows increasingly from online exchanges (Sousa, &amp; Ivanova 2012) more than any other media (for instance international press).

Task space adaptation via the learning of gait controllers of magnetic soft millirobots

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

Augmented Reality based Car Parking Application for Android

Today, Augmented Reality plays a vital role in the tech industry. This paper is based on Augmented Reality car application and is an important topic in R&amp;D. This application, enables to place and drive virtual cars in the real world. This paper briefly, discuss about introducing Augmented Reality application for “Android”, because not everybody can afford for an iPhone which has tons of AR applications. This is the reason why this optimised AR car application is made only for Android. It enables to place cars in real world with exact dimensions. The tools used to build this application are “UNITY” and “VUFORIA”. So, it gets easier to see whether a car can fit into a particular place or not, we can see how many cars can fit in a particular place and also, we can drive a car virtually to see whether it is possible to park a car in a congested place. It clearly shows that it saves time to park a car when compared to manual work. The result examined that real world interaction of car using Augmented Reality was successfully executed by placing multiple cars and in the mere future, there will be an update to move the car in all possible directions. It will play a major role in AR based research and also will be very useful for car buyers and also for the car companies.

Comparison of spatial orientation skill between real and virtual environment

Virtual reality (VR) is a promising tool and is increasingly used in many different fields, in which virtual walking can be generalized through detailed modeling of the physical environment such as in sports science, medicine and furthermore. However, the visualization of a virtual environment using a head-mounted display (HMD) differs compared to reality, and it is still not clear whether the visual perception works equally within VR. The purpose of the current study is to compare the spatial orientation between real world (RW) and VR. Therefore, the participants had to walk blindfolded to different placed objects in a real and virtual environment, which did not differ in physical properties. They were equipped with passive markers to track the position of the back of their hand, which was used to specify each object’s location. The first task was to walk blindfolded from one starting position to different placed sport-specific objects requiring different degrees of rotation after observing them for 15 s (0°, 45°, 180°, and 225°). The three-way ANOVA with repeated measurements indicated no significant difference between RW and VR within the different degrees of rotation (p > 0.05). In addition, the participants were asked to walk blindfolded three times from a new starting position to two objects, which were ordered differently during the conditions. Except for one case, no significant differences in the pathways between RW and VR were found (p > 0.05). This study supports that the use of VR ensures similar behavior of the participants compared to real-world interactions and its authorization of use.