Validation of a Tamil Version of the Five Facet Mindfulness Questionnaire Using Rasch Analysis.

Background: Various assessment tools that explore and assess mindfulness are available. Keeping in view both the origin of and the literature surrounding mindfulness assessment tools, this study aimed to evaluate the workability of one widely researched tool, the Five Facet Mindfulness Questionnaire (FFMQ), for establishing cross-cultural generalizability and utility in the Indian context. Methods: We recruited 303 adults over 18 with proficiency in the Tamil language and no history of significant neurological trauma and/or psychiatric history. They completed a version of the 39-item FFMQ, which we had translated into Tamil (FFMQ-T). The psychometric properties of this scale were tested using the Partial-Credit model of Rasch analysis. Results: Iterative Rasch analysis could not resolve consistent misfit of the Observe facet items. Using a subtest approach, a higher-order fit of the FFMQ-T could be achieved after the deletion of additional items from each of the remaining four facets. The resulting final model for the FFMQ-T questionnaire was a four-factor solution with 22 items. Conclusions: This study concluded the usability of the new 22-item FFMQ-T. These results are not dissimilar to the other versions in similar populations, such as the Hindi version of the FFMQ. The ordinal-to-interval conversion tables provided here ensure that the FFMQ-T can be used with enhanced precision and parametric statistics.

Exploring the utility of robots as distractors during a delay-of-gratification task in preschool children.

The development of executive function (EF) in children, particularly with respect to self-regulation skills, has been linked to long-term benefits in terms of social and health outcomes. One such skill is the ability to deal with frustrations when waiting for a delayed, preferred reward. Although robots have increasingly been utilized in educational situations that involve teaching psychosocial skills to children, including various aspects related to self-control, the utility of robots in increasing the likelihood of self-imposed delay of gratification remains to be explored. Using a single-case experimental design, the present study exposed 24 preschoolers to three experimental conditions where a choice was provided between an immediately available reward and a delayed but larger reward. The likelihood of waiting increased over sessions when children were simply asked to wait, but waiting times did not increase further during a condition where teachers offered activities as a distraction. However, when children were exposed to robots and given the opportunity to interact with them, waiting times for the majority of children increased with medium to large effect sizes. Given the positive implications of strong executive function, how it might be increased in children in which it is lacking, limited, or in the process of developing, is of considerable import. This study highlights the effectiveness of robots as a distractor during waiting times and outlines a potential new application of robots in educational contexts.

The time is ripe for robopsychology.

As robotic applications become increasingly diverse, more domains of human lives are being involved, now also extending to educational, therapeutic, and social situations, with a trend to even more complex interactions. This diversity generates new research questions that need to be met with an adequate infrastructure of psychological methods and theory. In this review, we illustrate the current lack of a sub-discipline in psychology to systematically study the psychological corollaries of living in societies where the application of robotic and artificial intelligence (AI) technologies is becoming increasingly common. We thus propose that organized efforts be made toward recognition of robopsychology as a sub-discipline so that the field of psychology moves away from isolated publications of robot- and AI-related topics to a body of knowledge that is able to meet the demands for change, as the world is preparing for the Fourth Industrial Revolution. We propose a definition of robopsychology that not only covers the study of the effects of robots on human behavior, but also of robots and AI themselves, as well as acknowledging how this sub-discipline may eventually be fundamentally changed through robots and AI. In this sense, our definition mirrors an already existing definition of the field of robophilosophy.

Terrain Perception Using Wearable Parrot-Inspired Companion Robot, KiliRo.

Research indicates that deaths due to fall incidents are the second leading cause of unintentional injury deaths in the world. Death by fall due to a person texting or talking on mobile phones while walking, impaired vision, unexpected terrain changes, low balance, weakness, and chronic conditions has increased drastically over the past few decades. Particularly, unexpected terrain changes would many times lead to severe injuries and sometimes death even in healthy individuals. To tackle this problem, a warning system to alert the person of the imminent danger of a fall can be developed. This paper describes a solution for such a warning system used in our bio-inspired wearable pet robot, KiliRo. It is a terrain perception system used to classify the terrain based on visual features obtained from processing the images captured by a camera and notify the wearer of terrain changes while walking. The parrot-inspired KiliRo robot can twist its head and the camera up to 180 degrees to obtain visual feedback for classification. Feature extraction is followed by K-nearest neighbor for terrain classification. Experiments were conducted to establish the efficacy and validity of the proposed approach in classifying terrain changes. The results indicate an accuracy of over 95% across five terrain types, namely pedestrian pathway, road, grass, interior, and staircase.