Emotional dysregulation and linguistic patterns as a defining feature of patients in the acute phase of anorexia nervosa
Bibliographic record
Abstract
PURPOSE: This research aims to analyze the relationship between emotional regulation and the symbolic process in autobiographical narratives of a group of individuals diagnosed with restrictive anorexia nervosa (AN), compared to a non-clinical group. The study is framed within multiple code theory (MCT) (Bucci, 1997; 2021), which considers mind-body integration. The purposes of this study are to investigate whether participants of the AN group will show greater alexithymia and emotional dysregulation than the non-clinical group; and whether the specific linguistic and symbolic features, such as somato-sensory words, affect words, and difficulty in the symbolizing process will predict the AN group. METHODS: Twenty-nine female participants hospitalized with AN during an acute phase (mean age 19.8 ± 4.1) and 36 non-clinical female participants (mean age 21 ± 2.4) were selected through snow-ball sampling. The participants completed the Toronto Alexithymia Scale (TAS-20), the Profile of Mood of State (POMS), the Emotion Regulation Questionnaire (ERQ), and the Relationship Anecdotes Paradigm Interview (RAP). The RAP interview was audio-recorded and transcribed to apply the Referential Process (RP) Linguistic Measures. A T test for paired samples and a logistic binary regression was performed. RESULTS: AN presented a significantly higher emotional dysregulation through the ERQ, TAS20 and POMS measures. Specifically, AN showed higher ER expression/suppression strategies, fewer functional cognitive strategies, higher alexithymia, and higher mood dysregulation. Specific linguistic features such as sensory-somatic, word affect, and difficulty in RP symbolizing predict the AN group (R2 = 0.349; χ2 = 27,929; df = 3; p = .001). CONCLUSIONS: Emotional dysregulation is connected to AN symptoms and autobiographical narratives. The results can help a clinical assessment phase showing specific linguistic features in AN patients. LEVEL OF EVIDENCE: Level II, controlled trial without randomization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".