A Mixed Methods Design to Detect Adolescent and Young Adults' Impulsiveness on Decision-Making and Motor Performance

Abstract

Impulsiveness in adolescents and young adults is an important aspect of psychological research. However, there still is lack of research that relates impulsiveness and motor performance in those. Thus, we aim to detect the levels of impulsiveness related to motor skills, motor laterality, spatial orientation, and individual interaction on the decision-making of adolescents and young adults across three staggered workouts. The study had 71 participants (53 males and 18 females), ranging in age from 17 to 24 years old ( M age = 18.5 years; SD = 1.72) and classified as non-impulsiveness ( n = 47), impulsiveness ( n = 17), and attention deficit hyperactivity disorder (ADHD) ( n = 7). A Mixed Methods research was conducted throughout four research tools (a) The Observational System of Motor Skills (OSMOS) was used to observe and detect the movement sequences patterns; (b) The Spanish version of Impulsive Behavior Scale (UPPS-P) was administered to obtain the impulsiveness profiles; (c) The Precision and Agility Tapping over Hoops (PATHoops) was carried out to observe the decision-making and temporal-spatial over movement effectiveness; (d) Motor Laterality Inventory (MOTORLAT) was applied to obtain the laterality profiles related to motor skills performance. This Mixed Methods approach has obtained useful results for impulsiveness in motor situations as the results from the different tools converge to established three clear profiles of impulsiveness. Participants with ADHD showed lack of interpersonal interaction, non-resolute decision-making, and lesser richness of motor skills patterns than non-impulsiveness and impulsiveness subjects. Additionally, impulsiveness participants also showed rich motor patterns, dyadic interactions, good decision making in spatial orientation tasks, and more versatile laterality in the lower limbs.

Optimizing Education: A Mixed Methods Approach Oriented to Teaching Personal and Social Responsibility (TPSR)

“…The integrated figures show that all teachers experienced a considerable shift in their teaching strategies from directive and controlling intervention, with negative assessments that generate reproduction responses from the students, toward participatory intervention that promotes autonomy responses from the students. The three methodological tools used in this study highlight the same process of pedagogical optimization that promotes student involvement and responsibility (Lorente and Kirk, 2016; Prat et al, 2019a,b).…”

“…A mixed methods approach was followed in this study: (a) the Observational System of Teaching Oriented Responsibility (OSTOR) adapted from the Spanish version SORPS (Prat et al, 2019a,b) was used to obtain teacher behavior patterns and (b) the Tool for Assessing Responsibility-Based Education 2.0. (TARE 2.0, Escartí et al, 2015) focused on perceived behaviors of teachers and students by two external observers based on the Tool for Assessing Responsibility-Based Education (TARE, Wright and Craig, 2011).…”

“…Because any basic time unit can be used, behavioral structures can be explored in detail and stronger connections between successive recorded behaviors are revealed. T-pattern detection has been successfully used in several research fields (Burgoon et al, 2016; Pérez-Tejera et al, 2018) to reveal hidden behaviors and underlying pedagogical actions (Castañer et al, 2010, 2013a; 2016b; Rodríguez-Dorta and Borges, 2017; Prat et al, 2019a). In sum, T-pattern detection is an analysis technique that scrutinizes all coded behaviors and their combinations, revealing which ones establish a behavior pattern that appears several times throughout the observed sessions.…”

Immune suppressive landscape in the human esophageal squamous cell carcinoma microenvironment

“…To enable a systematic analysis of immune cell populations, we normalized and pooled single-cell data from all samples and conducted unsupervised clustering to identify distinguishable populations. The whole procedure was performed using Seurat v3.0 with default parameters 17 . We annotated these populations using their canonical markers and successfully identified the major types of tumor-infiltrating immune cells as shown in other cancers, including T cells, NK cells, monocytes/macrophages, dendritic cells (DCs), B cells, plasma cells, and mast cells, as well as a very small fraction (1.31%) of other non-immune cells that were mixed in with the sorted cells (Fig.…”

T-Pattern Detection and Analysis of Football Players’ Tactical and Technical Defensive Behaviour Interactions: Insights for Training and Coaching Team Coordination

“…Moreover, the T-pattern detection and analysis (TPA) technique facilitates recognising recurrent patterns in information like behaviour events over time, which deals effectively with rare events contrary to the traditional statistical theory ( Magnusson, 2017 ). Recent studies using this technique have shown benefits in studying coordination and sports behaviours ( Camerino et al, 2012 ; Lapresa et al, 2013 , 2018 ; Amatria et al, 2017 , 2019 ; Castañer et al, 2017 ; Fernández-Hermógenes et al, 2017 ; Prat et al, 2019 ; Tarragó et al, 2019 ).…”