Refining the assessment of disrupted maternal communication: Using item response models to identify central indicators of disrupted behavior
Bibliographic record
Abstract
The Atypical Maternal Behavior Instrument for Assessment and Classification (AMBIANCE; Bronfman, Madigan, & Lyons-Ruth, 2009-2014; Bronfman, Parsons, & Lyons-Ruth, 1992-2004) is a widely used and well-validated measure for assessing disrupted forms of caregiver responsiveness within parent-child interactions. However, it requires evaluating approximately 150 behavioral items from videotape and extensive training to code, thus making its use impractical in most clinical contexts. Accordingly, the primary aim of the current study was to identify a reduced set of behavioral indicators most central to the AMBIANCE coding system using latent-trait item response theory (IRT) models. Observed mother-infant interaction data previously coded with the AMBIANCE was pooled from laboratories in both North America and Europe (N = 343). Using 2-parameter logistic IRT models, a reduced set of 45 AMBIANCE items was identified. Preliminary convergent and discriminant validity was evaluated in relation to classifications of maternal disrupted communication assigned using the full set of AMBIANCE indicators, to infant attachment disorganization, and to maternal sensitivity. The results supported the construct validity of the refined item set, opening the way for development of a brief screening measure for disrupted maternal communication. IRT models in clinical scale refinement and their potential for bridging clinical and research objectives in developmental psychopathology are discussed.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".