Examining Why Patients With Attention-Deficit/Hyperactivity Disorder Lack Adherence to Medication Over the Long-Term
Bibliographic record
Abstract
OBJECTIVE: To investigate the reasons why patients with attention-deficit/hyperactivity disorder (ADHD) adhere poorly to medications over the long term (≥ 1 year). DATA SOURCES: PubMed was reviewed for studies between 1997 and January 2015 citing the reasons for medication nonadherence using these main keywords: ADHD, amphetamine, methylphenidate, atomoxetine, guanfacine, clonidine, long term, and adverse effects. Non-English language articles were excluded as were those that had a follow-up of < 1 year. STUDY SELECTION: Of 1,137 entries, 41 published articles citing reasons for subject withdrawal from treatment were included. None were included for clonidine. DATA EXTRACTION: Similar reasons for drug or study withdrawal were grouped together for analysis using a normalized numerical average, while unique reasons were analyzed individually. RESULTS: Reasons for discontinuing Food and Drug Administration (FDA)-approved medication after 1 year included "own wish/remission/don't need" (19.9%; 95% CI, 9.0-30.80), "withdrew consent" (16.2%; 95% CI, 10.0-22.5), "adverse effects" (15.1%; 95% CI, 10.4-19.8) and "suboptimal effect" (14.6%; 95% CI, 8.5-20.6), with the most common adverse event being "reduction in weight/appetite" (19.2%; 95% CI, 5.1-33.4). Other important factors included age, long- versus short-acting medication, psychosocial stressors, and "stop feeling like him/herself" on medication. CONCLUSIONS: The reasons why patients do not adhere to stimulant medication remain poorly studied and understood, especially over the long term. Standardizing the way studies evaluate patients who stop treatment and including more qualitative measures should lead to better treatment outcome and adherence to medication over the long term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".