Development of ICF Core Sets to standardize assessment of functioning and impairment in ADHD: the path ahead
Bibliographic record
Abstract
In the study of health and quality of life in attention deficit/hyperactivity disorder (ADHD), it is of paramount importance to include assessment of functioning. The International Classification of Functioning, Disability and Health (ICF) provides a comprehensive, universally accepted framework for the description of functioning in relation to health conditions. In this paper, the authors outline the process to develop ICF Core Sets for ADHD. ICF Core Sets are subgroups of ICF categories selected to capture the aspects of functioning that are most likely to be affected in specific disorders. The ICF categories that will be included in the ICF Core Sets for ADHD will be determined at an ICF Core Set Consensus Conference, wherein evidence from four preliminary studies (a systematic review, an expert survey, a patient and caregiver qualitative study, and a clinical cross-sectional study) will be integrated. Comprehensive and Brief ICF Core Sets for ADHD will be developed with the goal of providing useful standards for research and clinical practice, and to generate a common language for the description of functioning in ADHD in different areas of life and across the lifespan.
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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 | 0.322 | 0.424 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.019 | 0.012 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.011 | 0.018 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 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".