Assessing Treatment Outcomes in Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
Article Abstract Objective: To review measures used to assess treatment response in patients with attention-deficit/hyperactivity disorder (ADHD) across the life span. Data Sources: Keyword searches of English-language articles in the PubMed database up to and including the May 4, 2011, index date were performed with the search strings (1) (attention deficit disorder with hyperactivity OR ADHD) AND (outcome assessment OR adaptation of life skills OR executive function ) and (2) (attention deficit disorder with hyperactivity OR ADHD) AND (function OR functioning OR quality of life ). Study Selection: Articles found through this search were then selected based on relevance to the topic area; no specific quality criteria were applied. Data Extraction: Narrative review. Results: The vast majority of studies assessing ADHD treatments have measured treatment response using ADHD symptom measures. Additional domains relevant for assessing treatment response among children and adults with ADHD include functional impairment, quality of life, adaptive life skills, and executive function. Validated rating scales exist for assessing these additional domains, but there has been minimal research evaluating the sensitivity of these instruments for detecting treatment response in pediatric and adult samples. Conclusions: Assessment of treatment outcomes in ADHD should move beyond symptom assessment to incorporate measures of functioning, quality of life, adaptive skills, and executive function, especially when assessing long-term treatment response. The authors recommend a potential battery and schedule of measures that could be used to more comprehensively assess treatment response in patients with ADHD. Prim Care Companion CNS Disord 2012;14(6):doi:10.4088/PCC.11r01336 © Copyright 2012 Physicians Postgraduate Press, Inc. Submitted: December 19, 2011; accepted May 11, 2012. Published online: November 29, 2012. Corresponding author: Jeffery N. Epstein, PhD, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, ML-10006, Cincinnati, OH 45229-3039 (jeff.epstein@cchmc.org).
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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 | 0.015 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".