Early-life adversities and adult attachment in depression and alexithymia
Bibliographic record
Abstract
Alexithymia is a personality construct characterized by difficulties in identifying and verbalizing feelings, a restricted imagination, and an externally oriented thinking style. As alexithymia shows marked overlap with depression, its independent nature as a personality construct is still being debated. The etiology of alexithymia is unknown, although childhood emotional neglect and attachment formation are thought to play important roles. In the FinnBrain Birth Cohort Study, experiences of early-life adversities (EA) and childhood maltreatment (CM) were studied in a sample of 2,604 men and women. The overlap and differences between depression and alexithymia were investigated by comparing their associations with EA types and adult attachment style. Alexithymia was specifically associated with childhood emotional neglect (odds ratio (OR) 3.8, p < .001), whereas depression was related to several types of EA. In depression co-occurring with alexithymia, there was a higher prevalence of emotional neglect (81.3% vs. 54.4%, p < .001), attachment anxiety (t = 2.38, p = .018), and attachment avoidance (t = 4.03, p < .001). Early-life adversities were markedly different in the alexithymia group compared to those suffering from depression, or healthy controls. Depression with concurrent alexithymia may represent a distinct subtype, specifically associated with childhood experiences of emotional neglect, and increased attachment insecurity compared to non-alexithymic depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".