Art therapy, as well as other arts-based therapies and interventions, is used to reduce pain, stress, depression, breathlessness and other symptoms in a wide variety of serious and chronic diseases, such as cancer, Alzheimer and schizophrenia. Arts-based approaches are also known to contribute to one’s well-being and quality of life. However, much research is required, since the mechanisms by which these non-pharmacological treatments exert their therapeutic and psychosocial effects are not adequately understood. A typical clinical setting utilizing the arts consists of the creation work itself, such as the artwork, as well as the therapist and the patient, all of which constitute a rich and dynamic environment of occurrences. The underlying complex, simultaneous and interwoven processes of this setting are often considered intractable to human observers, and as a consequence are usually interpreted subjectively and described verbally, which affect their subsequent analyses and understanding. We introduce a computational research method for elucidating and analyzing emergent expressive and social behaviors, aiming to understand how arts-based approaches operate. Our methodology, which centers on the visual language of Statecharts and tools for its execution, enables rigorous qualitative and quantitative tracking, analysis and documentation of the underlying creation and interaction processes. Also, it enables one to carry out exploratory, hypotheses-generating and knowledge discovery investigations, which are empirical-based. Furthermore, we illustrate our method’s use in a proof-of-principle study, applying it to a real-world artwork investigation with human participants. We explore individual and collective emergent behaviors impacted by diverse drawing tasks, yielding significant gender and age hypotheses, which may account for variation factors in response to art use. We also discuss how to gear our research method to systematic and mechanistic investigations, as we wish to provide a broad empirical evidence for the uptake of arts-based approaches, also aiming to ameliorate their use in clinical settings.

Music making, in the form of free improvisations, is a common technique in music therapy, used to express one’s feelings or ideas in the non-verbal language of music. In the broader sense, arts therapies, and music therapy in particular, are used to induce therapeutic and psychosocial effects, and to help mitigate symptoms in serious and chronic diseases. They are also used to empower the wellbeing and quality of life for both healthy individuals and patients. However, much research is still required to understand how music-based and arts-based approaches work, and to eventually enhance their effectivity. The clinical setting employing the arts constitutes a rich dynamic environment of occurrences that is difficult to capture, being driven by complex, simultaneous, and interwoven behavioral processes. Our computational paradigm is designed to allow substantial barriers in the arts-based fields to be overcome by enabling the rigorous and quantitative tracking, analyzing and documenting of the underlying dynamic processes. Here we expand the method for the music modality and apply it in a proof of principle experimentation to study expressive behavioral effects of diverse musical improvisation tasks on individuals and collectives. We have obtained statistically significant results that include empirical expressive patterns of feelings, as well as proficiency, gender and age behavioral differences, which point to variation factors of these categorized collectives in music making. Our results also suggest that males are more exploratory than females (e.g., they exhibit a larger range of octaves and intensity) and that the older people express musical characterized negativity more than younger ones (e.g., exhibiting larger note clusters and more chromatic transitions). We discuss implications of these findings to music therapy, such as behavioral diversity causality in treatment, as well as future scientific and clinical applications of the methodology.

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Art therapy and music therapy, as well as other arts-based approaches and interventions, help to mitigate symptoms in serious and chronic diseases and to improve the well-being and quality of life for both healthy individuals and patients. Artistic creation is also researched and practiced intending to empower and understand individuals, groups, and communities. However, much research is required in order to learn how arts-based approaches operate and to enhance their effectivity. The complex and simultaneous occurrences involving the dynamics of the creation work, the client, and the therapist in a typical arts setting are difficult to grasp, consequently affecting their objective analyses. Here we employ our Computational Paradigm which enables the quantitative and rigorous tracking, analyzing, and documenting of the underlying dynamic processes, and describe its application in recent past and current real-world art and music studies with human participants. We aim to study emergent artistic behaviors of individuals and collectives in response to art and music making. Significant insights obtained include demographic variation factors such as gender and age, empirical behavioral patterns, and quantitative expressiveness and its change. We discuss the implications of the findings for therapy and research, such as causality for behavioral diversification and audio-visual cross-modality, and also offer directions for future applications and technology enhancements.

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