Early maladaptive schemas and child and adult attachment: A 15‐year longitudinal study
Bibliographic record
Abstract
OBJECTIVES: To examine the relation between early maladaptive schemas (EMS), as defined in schema therapy, and both child and adult attachment. DESIGN: A 15-year longitudinal design in which child attachment groups (secure, avoidant, ambivalent, and disorganized) were compared in early adulthood on their profile of scores across EMS domains. A similar strategy was used to examine EMS profiles as a function of adult attachment groups (secure, preoccupied, and fearful). METHODS: Sixty participants, recruited from Montreal day-care centres, were assessed at 6 (Time 1) and 21 years of age (Time 2). Time 1 attachment was assessed using a separation-reunion procedure and Time 2 attachment, using the Experiences in Close Relationships questionnaire. EMS were evaluated with the Young Schema Questionnaire (Time 2). RESULTS: There were more signs of EMS among young adults with either an insecure ambivalent child attachment, or an insecure preoccupied adult attachment style, compared to their secure peers. These differences were not specific to one domain of EMS; they were reported for various EMS. CONCLUSIONS: The results suggest that specific elements of representational models are more likely to be related to the development of EMS: high anxiety over abandonment, negative self-view, and explicit manifestations of personal distress. Unmet childhood needs for secure attachment may lead to a large variety of EMS as defined in schema 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".