Evaluating the use of the AMBIANCE‐Brief measure in clinical settings: Assessing acceptability, feasibility, and utility of the AMBIANCE‐Brief
Bibliographic record
Abstract
Community agencies and practitioners around the globe seek opportunities to learn various assessment tools and interventions rooted in attachment theory. However, information regarding the feasibility of implementation and sustainability of these tools once participants have been trained to use them, is limited. This study investigated the perceived acceptability, feasibility, utility, relevance, fidelity, and sustainability of the Atypical Maternal Behavior Instrument for Assessment and Classification-Brief (AMBIANCE-Brief) among practitioners who had taken a training. Practitioners (N = 59) who attended a virtual AMBIANCE-Brief training originating from Canada between June 2020 and November 2021 completed an online follow-up survey. Practitioners reported that they primarily used the AMBIANCE-Brief for case conceptualization (68%). Additionally, 95% agreed that the AMBIANCE-Brief was relevant to their clinical practice, 98% agreed it was useful for their clinical work, 76% agreed that it was feasible to implement into their clinical work, and 59% found it easy to incorporate into their treatment planning with clients. Findings suggest that the AMBIANCE-Brief may be acceptable, feasible, and useful for practitioners. Avenues for continuing to evaluate the AMBIANCE-Brief include cross-cultural validity, coder drift, and booster sessions. Additional work clarifying how practitioners integrate the measure into practice would be valuable.
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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 | 0.077 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".