Latent profiles of maternal disrupted communication: Relations to affect and behaviour in early infancy
Bibliographic record
Abstract
Few studies have examined how mothering is organized in the first months of infancy, especially regarding risk-related interactions. Person-centred approaches, including latent profile analysis (LPA), add valuable insights about early parenting by identifying distinct profiles of interaction. First, this study aimed to identify profiles of disrupted maternal interaction during the Still-Face Paradigm among 181 mothers and their 3- to 8-month-old infants. Second, the study assessed how each maternal profile was related to infant affect and interactive behaviour. The LPA identified four profiles of maternal interaction: optimal, negative/intrusive, withdrawing and pervasively disrupted. The pervasively disrupted profile, in particular, has not been identified in past research. Each profile was associated with specific aspects of infant affect and behaviour. Recognition of disrupted behavioural profiles among at-risk mothers and infants in the early months could facilitate more precise tailoring of early interventions to the needs of mothers and infants with differing profiles of interactive risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".