Differences in Levels of Functional Impairment and Rates of Serious Emotional Disturbance Between Youth With Internalizing and Externalizing Disorders When Using the CAFAS or GAF to Assess Functional Impairment
Bibliographic record
Abstract
This investigation examined how two commonly employed measures of functional impairment (the Child and Adolescent Functional Assessment Scale [CAFAS] and the Global Assessment of Functioning [GAF] scale) perform with respect to assessing levels of functional impairment and, hence, identifying rates of serious emotional disturbance (SED) across youth diagnosed with internalizing or externalizing disorders. GAF scores indicated comparable levels of functional impairment between groups. CAFAS scores suggested significantly higher levels of functional impairment for youth diagnosed with externalizing disorders. The CAFAS also identified significantly higher rates of SED among youth with externalizing than those with internalizing disorders, whereas the GAF identified comparable rates of SED between groups. These findings suggest caution when relying on a single measure to assess functional impairment and to identify SED, particularly when these measures are used in decisions concerning service allocation. Implications of these findings are addressed, including the need for further research to identify the optimal assessment strategy to assess functional impairment and identify SED among youth diagnosed with internalizing or externalizing disorders.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".