A systematic review of attention‐deficit/hyperactivity disorder in people living with cystic fibrosis
Bibliographic record
Abstract
There is a lack of research that has focused on attention-deficit hyperactivity disorder (ADHD) in people with cystic fibrosis (pwCF). Given ADHD is associated with executive functioning impairments, exploring ADHD in the context of living with cystic fibrosis (CF) is of great importance. The purpose of the current systematic review was to examine ADHD in pwCF across the lifespan in terms of its prevalence, its impact on various health outcomes, and treatments for managing ADHD. This systematic review followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Articles reporting studies of any design that focused on ADHD in pwCF were included. Studies were excluded if they did not meet this criterion and if they were written in languages other than English. PsycINFO, MEDLINE, EMBASE, and CINAHL databases were searched. Search items were based on three concepts: (1) terms related to CF, (2) terms related to ADHD, and (3) terms related to age. Ten studies were included in this systematic review. Reported prevalence rates of ADHD in pwCF ranged from 5.26% to 21.9%. The reported relationships between ADHD and CF and other health outcomes is inconsistent. In terms of treatment considerations, pharmacological interventions and behavioural strategies for managing ADHD in the context of living with CF have been reported as being successful. Additional research is needed to further explore ADHD in the CF population and health variables that may be associated with CF prognosis.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".