Research Areas

 

In this section, we aim to outline the primary areas of research that we focus on. We've provided brief descriptions for each area. You can find corresponding publications in the Publications section for each of these areas.

  Formal Psychological Assessment (FPA)

Since 2007, the QPLab has been developing a methodology for psychological assessment based on methods borrowed from mathematical psychology such as Knowledge Space Theory (Falmagne & Doignon, 1999) and Formal Concept Analysis (Ganter & Wille, 1999). This methodology has been named Formal Psychological Assessment (e.g., Spoto, 2011; Spoto, Bottesi, Sanavio, Vidotto, 2013) and allows for the development of adaptive assessment tools, both of self-report type (e.g., Spoto, Serra, Donadello, Granziol, & Vidotto, 2018) and observational (e.g., Granziol, Brancaccio, ..., Vidotto, & Spoto, 2022). At the core of the methodology is the possibility to identify, for each item, a set of symptoms of the investigated issue that it assesses. From this "formal context", a lattice is obtained, which serves as the starting point for the probabilistic and adaptive implementation of the procedure.

  Statistical analysis and psychological methods

The research activities of the QPLab rely on the study and application of advanced statistical methodologies and techniques to perform data analysis in several fields, both in cross-sectional and longitudinal studies, spanning from single-case studies to large samples. These methodologies include linear and non-linear models.

  Inter rater agreement

The evaluation of agreement among experts in a classification task is crucial in many situations. Traditional indexes used to estimate interrater agreement (such as Cohen’s j) simply count the number of observed agreements and correct them by removing chance agreements. We propose a new theoretical framework for the evaluation of interrater agreement based on the possibility of adjusting the observed classifications conducted by the raters. This framework refers to the introduction and formalization of two concepts involved in the classification task: (a) the belonging measure of an object to a category and (b) the rater’s belonging threshold, which is the minimally sufficient value of the belonging measure at which the rater will classify an object into a category. These factors are ignored by traditional indexes for interrater agreement, though their role may be decisive. A certain number of papers follow this initial approach (cfr. Spoto,  Nucci, Prunetti, & Vicovaro, 2023; Nucci, Spoto, Altoè, & Pastore 2021; Bruno,  Vicovaro, Nucci, Cropanise,  Fabbian, Mondin, ... & Spoto 2023).

  Mathematical Psychology

The QPLab is very active in research in mathematical psychology. In particular, it has focused on the formal and theoretical development of the Knowledge Space Theory (KST), with specific attention to issues of identifiability of knowledge structures in the application of the basic local independence model (e.g., Spoto, Stefanutti, & Vidotto, 2012, 2013; Stefanutti, Spoto & Vidotto, 2018). It has also been involved in constructing knowledge structures from empirical data (e.g., de Chiusole, Spoto, & Stefanutti, 2020; Spoto, Stefanutti, & Vidotto, 2016), extending the KST to the polytomous case both in its deterministic part (e.g., Stefanutti, Anselmi, de Chiusole, & Spoto, 2020) and its probabilistic part (e.g., Stefanutti, de Chiusole, Anselmi, & Spoto, 2020). Recently, the phenomenon of "empirical indistinguishability" of knowledge structures (Stefanutti & Spoto, 2021) and "skill maps" (Spoto & Stefanutti, 2023) has been studied. Members of the QPLab have also been interested in the connection between KST models and Item Response Theory models (e.g., Noventa, Ye, Kelava, & Spoto, 2024).

  Assessment tools in clinical and health psychology

This research line focuses on the development, refinement, and validation of psychological assessment tools applicable across diverse fields, including health psychology, clinical psychology, and rehabilitation psychology. Particular emphasis is placed on ensuring construct validity, encompassing facets such as content validity, structural validity, and discriminant validity. Various theoretical frameworks are explored, including Classical Test Theory, Item Response Theory, and methodologies from Network Psychometrics. Additionally, emerging theoretical approaches from mathematical psychology, such as FPA, enable the creation of adaptive and efficient assessment tools.

  Traffic psychology, road users’ safety and driving behavior

The investigation of human behavior and of human interactions in complex scenarios is a well-known research field in psychology. As active actors of the urban environment, individuals are required to deal with usually tangled road traffic in different situations and from different perspectives (as car/motor drivers, as cyclists or even as pedestrians). The traffic psychology research fields delve into this complex topic with the aim of improving road users’ safety by studying how people plan, perform and react to critical situations in the urban environment. The QPLab is active on the development of behavioral models, psychometric tools and experimental designs to study these aspects both from the theoretical and the applicative perspectives, taking advantage of driving simulators, psychophysiological tools, virtual reality settings (VRs, CAVE Lab) and several academic collaborations (e.g., MoBe research center, DIATI - Department at Politecnico di Torino, etc).

  Morality and ethics of autonomous systems

The transition towards autonomous transportation is fueling both academic and public debate, while changing urban landscapes and our idea of integrated mobility. The relation with autonomous vehicles (AVs) will require individuals to overcome a series of psychological roadblocks and misconceptions, as well as reconcile with personal and collective moral norms. The investigation of moral judgment and social evaluation of the upcoming AV’s behavior - especially in critical situations - requires the adoption of reliable experimental methods and statistical techniques. The psychological constructs investigated in this field are directly and indirectly related with automated mobility, also resulting in the acceptance, propension and morality towards the use of autonomous systems in the broader context.

  Functional Measurement and Information Integration Theory

Information Integration Theory posits that individuals integrate various pieces of information using simple algebraic rules such as addition and multiplication when making judgments across different domains. Functional measurement serves as a robust methodological tool for assessing these rules. At the QPlab, we focus on theoretical, methodological, and application-oriented aspects of Information Integration Theory and Functional Measurement.

  Intuitive physics

Intuitive physics investigates how individuals without formal physics education intuitively reason about physical phenomena. It offers insights into how people construct their internal models of the world, revealing common biases that impede students' comprehension of elementary physics. Our research focuses on refining methodologies for studying intuitive physics, particularly examining people's perception and comprehension of fundamental physical principles such as gravitational motion and collisions. 

  Space-magnitudes associations

Research indicates that magnitudes such as numbers, time, and loudness are spontaneously mapped onto space by the cognitive system. In Western cultures, there is a tendency to associate larger magnitudes with the right side of space and smaller magnitudes with the left side. In addition to investigating the spatial representation of various magnitudes such as weight, time, and economic value along both horizontal and vertical dimensions of space, our work involves optimizing statistical techniques for analyzing associations between space and magnitude.