An Attachment-Based Model of the Relationship Between Childhood Adversity and Somatization in Children and Adults
Bibliographic record
Abstract
OBJECTIVE: An attachment model was used to understand how maternal sensitivity and adverse childhood experiences are related to somatization. METHODS: We examined maternal sensitivity at 6 and 18 months and somatization at 5 years in 292 children in a longitudinal cohort study. We next examined attachment insecurity and somatization (health anxiety, physical symptoms) in four adult cohorts: healthy primary care patients (AC1, n = 67), ulcerative colitis in remission (AC2, n = 100), hospital workers (AC3, n = 157), and paramedics (AC4, n = 188). Recall of childhood adversity was measured in AC3 and AC4. Attachment insecurity was tested as a possible mediator between childhood adversity and somatization in AC3 and AC4. RESULTS: In children, there was a significant negative relationship between maternal sensitivity at 18 months and somatization at age 5 years (B = -3.52, standard error = 1.16, t = -3.02, p = .003), whereas maternal sensitivity at 6 months had no significant relationship. In adults, there were consistent, significant relationships between attachment insecurity and somatization, with the strongest findings for attachment anxiety and health anxiety (AC1, β = 0.51; AC2, β = 0.43). There was a significant indirect effect of childhood adversity on physical symptoms mediated by attachment anxiety in AC3 and AC4. CONCLUSIONS: Deficits in maternal sensitivity at 18 months of age are related to the emergence of somatization by age 5 years. Adult attachment insecurity is related to somatization. Insecure attachment may partially mediate the relationship between early adversity and somatization.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".