The McMaster family assessment device and clinical rating scale: Questionnaire vs interview in childhood traumatic brain injury
Bibliographic record
Abstract
Two modalities of family assessment based on the McMaster Model of Family Functioning (MMFF), including a self-report questionairre (Family Assessment Device-FAD) and a clinical interview (McMaster Structured Interview For Families-McSIFF) as scored on the McMaster Clinical Rating Scale (MCRS) were compared in an attempt to explore the inter-changeability of the two. Significant correlations were hypothesized between the FAD and MCRS in both prospective and retrospective groups and that correlations would increase over three data points in the prospective study. The sample included 50 children and adolescents (ages 6-4) with traumatic brain injury (TBI) from a prospective study. In addition, 72 children and adolescents (ages 5-14), consisting of 24 patients with severe TBI, individually matched to a comparison group of 24 mild TBI patients and a control group of 24 orthopaedic patients were included from a retrospective study. Significant correlations between the FAD and MCRS were found across both studies, with increasing correlations at each successive data point in the prospective study. Agreement between the two measures regarding classification of families as clinical vs healthy was also statistically significant at the majority of assessment occasions; however, most specific indices of agreement were only modest. The clinical and research implications of these findings are discussed.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".