Traumatic experiences, alexithymia, and posttraumatic symptomatology: a cross-sectional population-based study in Germany
Bibliographic record
Abstract
OBJECTIVE: Previous studies have established an association between number of traumatic experiences and alexithymia. The present study examines this relationship in a large-scale representative sample of the German general population (N=2,507) and explores the potential mediating effects of posttraumatic symptomatology, particularly avoidance/numbing. METHODS: Alexithymia was assessed with the German version of the Toronto Alexithymia Scale (TAS-20). Posttraumatic symptomatology was operationalized by the symptom score of the modified German version of the Posttraumatic Symptom Scale, and traumatic experiences were assessed with the trauma list of the Munich Composite International Diagnostic Interview. Two mediation analyses were conducted. RESULTS: Of the total sample, 24.2% (n=606) reported at least one traumatic experience, 10.6% (n=258) were classified as alexithymic, and 2.4% (n=59) fulfilled the criteria of posttraumatic stress disorder (PTSD). Participants who had survived five or more traumatic experiences had significantly higher alexithymia sum scores. The PTSD symptom cluster avoidance/numbing mediated the association between the number of traumatic experiences and alexithymia. CONCLUSIONS: Our findings illustrate an association between number of traumatic experiences and alexithymia and the influence of emotional avoidance and numbing within this relationship. The significant relationship between alexithymia and number of traumatic experiences in a general population sample further supports the concept of multiple and complex traumatization as associated with alexithymia. The results suggest the importance of further investigations determining the causal impact of alexithymia both as a potential premorbid trait and as consequence of traumatization. Lastly, future investigations are needed to clarify alexithymia as a distinct trauma-relevant characteristic for better diagnostics and specialized trauma-integrative therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".