How do mothers with borderline personality disorder mentalize when interacting with their infants?
Bibliographic record
Abstract
Mothers with borderline personality disorder (BPD) have been theorized to have decreased mentalization ability, which is the capacity to perceive and interpret mental states. This could increase the risk for troubled relationships with their infants and therefore have adverse consequences for child social and emotional development. Mind-mindedness (MM), which codes the mother's references to her infant's mental states during an interaction, is one method of indexing mothers' mentalizing ability. However, research has yet to examine MM in mothers with BPD. Our objective was to assess the MM ability of 38 mothers during interactions with their 12-month-old infants, including 10 mothers with BPD and 28 mothers without a psychiatric diagnosis. Trained observers assessed maternal MM from 2 min of videotaped mother-infant free play. BPD was assessed with the Structured Clinical Interview for DSM-III-R-Personality Disorders (SCID-II). Mothers with and without BPD did not differ in the proportion of total comments referring to infant mental states. However, mothers in the BPD group proportionately made 3.6 times more misattuned mind-related comments than control mothers. Thus, mothers with and without BPD appear equally likely to envision mental states in their infants. However, mothers with BPD also appear more likely to misread their infants' mental states. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".