Abstract
Emotional Textual Analysis (ETA) is a psychoanalytically informed method of text and discourse analysis that was developed in the 1980s as a tool for psychological research and intervention with social groups, institutions, and organizations. ETA hypothesizes that emotions expressed in language are a fundamental organizer of relationships. By detecting clusters of emotionally dense words within a text (through a procedure that combines quantitative—software supported—and qualitative data analysis), this method enables the exploration of the unconscious emotional dynamics underpinning processes of sense-making within social groups and organizations. This chapter aims to discuss the contribution that the ETA methodology can offer today to mental health studies. We will present two case studies. (a) In the first one, ETA served to shed light on a new issue that has arisen in the mental health field: an unprecedented increase over the last few decades in psychiatric diagnosis related to children’s difficulties at school. (b) In the second one, ETA was used within the framework of a 3-year intervention-research with a healthcare organization providing services for adult disability. The organization was stuck in a growing conflict with the family members of the service users. Our results corroborate the hypothesis that contemporary mental health risks—as well as demands and developmental trajectories—cannot be understood by looking solely at the individual; it is crucial to bring them back into the current dynamics of social coexistence, by means of methodologies that allow us to study the relationship between individuals and changing social contexts.
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Notes
- 1.
Fornari’s theory of affective codes (1976) builds on Melanie Klein’s object relations theory, in which we find for the first time a distinction between internal and external objects.
- 2.
All the interviewees’ associations, references, and the new connections they establish starting from the proposed question are significant for the detection of the emotional sense organizing their discourse, while the narrative coherence of their speech is deemed irrelevant in this kind of analysis.
- 3.
Depending on the context, a word may acquire particular emotional relevance. Thus, the dense words’ selection is guided by knowledge of the local research context.
- 4.
To be precise, these programs cut the text into segments of similar length (sentences or fragments of sentences called Elementary Context Units, ECUs), which are automatically delimited by punctuation. Thus, once the dense words have been isolated and the context units delimited, the software constructs a matrix crossing ECUs and dense words. On this matrix the program conducts a cluster analysis (based on a factorial correspondence analysis) designed to classify the context units according to the similarity or dissimilarity of the words occurring in them so as to map the most significant lexical repertoires in the text. For each cluster we have a list of the dense words that characterize it, ordered by chi−square value (χ2). The larger this value, the more significant the occurrence of the word within the ECUs belonging to that cluster. This means that the words with larger χ2 in each cluster are those that most significantly distinguish one cluster from the other. We know also how the different clusters are in relation to the so−called illustrative variables, that is socio−demographic and other structural variables characterizing the interviews or the interviewees in a study (for greater detail on the ETA procedure see Carli & Paniccia, 2002; Carli et al., 2016).
- 5.
A comprehensive description of ETA’s analytic models can be found in Carli and Paniccia (2002).
- 6.
The models included in this area describe a range of emotional dynamics whose common thread is to put barriers against the experience of foreignness which is inevitably implied in any social experience, such as the dynamics of provoking, controlling, reclaiming, possessing, mistrusting, complaining, feeling obligated.
- 7.
Models in this area include for example the emotional difference between compliance and commitment in organizational life or the difference between the organization experienced as a given entity or as a constructed entity.
- 8.
Factorial correspondence analysis is a multivariate statistical technique developed by Benzécri and his research team, starting from the 1960s, particularly in order to study linguistic and textual data. More exactly, ETA uses multiple correspondence analysis, which enables the detection of underlying structures in a data set, by representing data as points in a multidimensional Euclidean space.
- 9.
Education in Italy is compulsory from 6 to 16 years of age.
- 10.
- 11.
As stated above, we call socio−demographic and other structural variables characterizing the interviews and the groups interviewed in a study illustrative variables: in this study, we took the different levels of education as an illustrative variable. Unlike dense words, these variables do not enter actively in the formation of the clusters. Nonetheless, the software that we use to support the quantitative part of ETA estimates the extent to which the different clusters of dense words are connected to the illustrative variables (this relation is also expressed in terms of chi−square value), which indicates, in our case, that certain associations between words occur more frequently in the speech of teachers who work in the primary school, for example, or in the secondary school, and so on. If there are no statistically significant relationships with the illustrative variables, this means the cluster concerned has a wider relevance.
- 12.
We have devoted several works over the years to investigating the education systems’ problems (Carli, Dolcetti, Giovagnoli, Gurrieri, & Paniccia, 2015; Giovagnoli, Caputo, & Paniccia, 2015; Paniccia, 2012a, 2012b, 2013; Paniccia, Giovagnoli, Bucci, & Caputo, 2014: Paniccia, Giovagnoli, Di Ruzza, & Giuliano, 2014).
- 13.
We use “inward-looking” to describe the tendency of an organization to function as a closed system, that is a system tending to assimilate any variability connected to the relationship with the external reality (including the relationship with the users/clients) in terms of an internal operative model designed to pursue given organizational patterns (Bucci & Vanheule, 2018; Thompson, 1967).
- 14.
- 15.
Disability is part of a tripartite system that includes also impairment and handicap. Impairment is defined as “any loss or lack of any physiological, anatomical, psychological structure or function”; handicap is instead defined as “a disadvantage, for an individual, caused by an impairment or a disability, that limits or prevents the assumption of a role considered normal (in regards to age, sex, social and cultural factors) for that individual” (World Health Organization, 1980, p. 183). As in the case of the psychiatric syndromes of the DSM V (which includes intellectual disability), this is a categorial system that tends to be inward-looking since there is no external validator of the classification system itself (Di Ninni, 2004).
- 16.
GAP was founded by Felice Bisogni and Stefano Pirrotta and provides organizational consultancy services for public bodies and third sector organizations (www.apsgap.it).
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Bucci, F. et al. (2021). Bringing Mental Health Back into the Dynamics of Social Coexistence: Emotional Textual Analysis. In: Borcsa, M., Willig, C. (eds) Qualitative Research Methods in Mental Health. Springer, Cham. https://doi.org/10.1007/978-3-030-65331-6_9
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