Indirect observation is a recent concept in systematic observation. It largely involves analyzing textual material generated either indirectly from transcriptions of audio recordings of verbal behavior in natural settings (e.g., conversation, group discussions) or directly from narratives (e.g., letters of complaint, tweets, forum posts). It may also feature seemingly unobtrusive objects that can provide relevant insights into daily routines. All these materials constitute an extremely rich source of information for studying everyday life, and they are continuously growing with the burgeoning (...) of new technologies for data recording, dissemination, and storage. Narratives are an excellent vehicle for studying everyday life, and quantitization is proposed as a means of integrating qualitative and quantitative elements. However, this analysis requires a structured system that enables researchers to analyze varying forms and sources of information objectively. In this paper, we present a methodological framework detailing the steps and decisions required to quantitatively analyze a set of data that was originally qualitative. We provide guidelines on study dimensions, text segmentation criteria, ad hoc observation instruments, data quality controls, and coding and preparation of text for quantitative analysis. The quality control stage is essential to ensure that the code matrices generated from the qualitative data are reliable. We provide examples of how an indirect observation study can produce data for quantitative analysis and also describe the different software tools available for the various stages of the process. The proposed method is framed within a specific mixed methods approach that involves collecting qualitative data and subsequently transforming these into matrices of codes (not frequencies) for quantitative analysis to detect underlying structures and behavioral patterns. The data collection and quality control procedures fully meet the requirement of flexibility and provide new perspectives on data integration in the study of biopsychosocial aspects in everyday contexts. (shrink)

Deception has evolved to become a fundamental aspect of human interaction. Despite the prolonged efforts in many disciplines, there has been no definite finding of a univocally “deceptive” signal. This work proposes an approach to deception detection combining cognitive load manipulation and T-pattern methodology with the objective of: (a) testing the efficacy of dual task-procedure in enhancing differences between truth tellers and liars in a low-stakes situation; (b) exploring the efficacy of T-pattern methodology in discriminating truthful reports from deceitful ones (...) in a low-stakes situation; (c) setting the experimental design and procedure for following research. We manipulated cognitive load to enhance differences between truth tellers and liars, because of the low-stakes lies involved in our experiment. We conducted an experimental study with a convenience sample of 40 students. We carried out a first analysis on the behaviors’ frequencies coded through the observation software, using SPSS (22). The aim was to describe shape and characteristics of behavior’s distributions and explore differences between groups. Datasets were then analyzed with Theme 6.0 software which detects repeated patterns (T-patterns) of coded events (non-verbal behaviors) that regularly or irregularly occur within a period of observation. A descriptive analysis on T-pattern frequencies was carried out to explore differences between groups. An in-depth analysis on more complex patterns was performed to get qualitative information on the behavior structure expressed by the participants. Results show that the dual-task procedure enhances differences observed between liars and truth tellers with T-pattern methodology; moreover, T-pattern detection reveals a higher variety and complexity of behavior in truth tellers than in liars. These findings support the combination of cognitive load manipulation and T-pattern methodology for deception detection in low-stakes situations, suggesting the testing of directional hypothesis on a larger probabilistic sample of population. (shrink)

Soccer players inescapably live under stress during the sportive career, and many real-life aspects of soccer situations operate in the ongoing performance. This study’s main objective was to elaborate the List of Stressors in Professional Indoor and Field Soccer, a self-report instrument designed to measure the impact of 77 soccer situations upon the sport performance. Participants were 138 indoor and field soccer players from the Brazilian Premier League. Each situation was evaluated on a 7-point scale, ranging from the most negative (...) to the most positive. Data were analyzed according to the players’ perception of the items: distress or eustress and its intensity, and after that, situations perceived as plus −1 and +1 were compared by time in which they were experienced and distributed among five categories established by the literature: Expectations about the Performance, Personal Factors, Competition Aspects, Training Demands, and Relationship with Significant People. Narratives of athletes’ experiences were also used to discuss the results. An Exploratory Structural Equation Modeling using Bi-factorial was employed to assess the factor structure. For the total participants, 49 situations were perceived as distress and 28 as eustress. Using the criteria established a priori, the distribution was among the five categories in the remaining 32 situations. Differences in perception between less and more experienced players were found in 11 situations. The results revealed that Brazilian professional soccer players experience various stressful situations. These events are important representations of environmental demands and could predict the performance as they are perceived as eustress or distress. Some of these stressful situations are inherent in sport and others adjacent to the sports system or environment. Coach pressure to win and conflicts with teammates are examples of stressors in-sport, family problems and disputes with press or fans are examples of stressors external to the team, also called peripheral opponents, and showed the relative social influence of significant others in soccer performance. We can conclude that the knowledge of the direction of a given stress situation has important practical implications in preparing athletes and helping them face the performance stressors that are part of soccer daily life. (shrink)