Toward the Automation of Family Semantic Grids: a Pilot Exploration of Text Mining for Evidence-Informed Systemic-Relational Psychotherapy

IntroductionRetracing the theme of what can legitimately be considered “evidence” in psychotherapy, the present work shows the application of an ad hoc, rule-based text mining program specifically designed to analyze therapy session transcripts. Developed within a systemic-relational framework, and grounded in Semantic Polarities Theory, the program works through a hybrid human-in-the-loop approach and provides data for subsequent descriptive and inferential analyses on meaning transformation starting from consultation sessions.ParticipantsThe present study examines the clinical case of an adolescent girl with untreated past non-suicidal self-injury (NSSI) and suicidal ideation. Before moving to the joint family work phase, family therapy consultation was conducted in separate sessions within an alternating parent-adolescent format.MethodsOverall semantic activity was compared across events with Wilcoxon rank-sum tests. In categorical comparisons, data were analyzed using chi-square tests, with df-scaled Cramer's V to measure effect sizes and Monte Carlo p-values. Initial subjects' positioning profile across Family Semantic Grids (FSGs) was described using semantic heatmaps and main polarities use. Linear Mixed-Effects (LME) models were implemented to track longitudinal changes in the subjects' positioning, specifically investigating the therapist's influence.ResultsResults indicated that the therapist introduced a significantly lower proportion of new meanings across all comparisons during the consultation phase. LME models showed significant intensity shifts toward positive-valued meanings, supported by ICC, Rm2 and Rc2 values, and inform on the significant specific use of Narrated Semantic Polarities (NSP) and Interactive Semantic Polarities (ISP) across participants.DiscussionOverall, the study supports the feasibility of a semi-automated process for coding and for subsequent analyses of family semantic polarities. In fact, performed analyses demonstrate how therapist positioning and meaning management through re-expression and semantic shifts significantly influenced family members' change in positioning, an effect especially evident for the identified patient. In conclusion, rule-based text mining can yield process indicators that remain clinically legible. Read as “semantography,” results provide a compact, data-grounded map of coupling and early change while staying parsimonious on case disclosure. Limits and future directions of the present pilot study are discussed.