A-141 Vindicated by Awareness: Acting with Awareness May Compensate for Inhibitory Deficits in ADHD Symptom Burden
Bibliographic record
Abstract
Abstract Objective To understand the role of trait mindfulness acting-with-awareness in the relationship between inhibitory control and ADHD symptom burden. Method We conducted a cross-sectional study with 103 adults, aged 18 to 86, mean age = 46, mean education = 15 years, 46% male. Participants were recruited in North Western Oregon counties. Eligible individuals were aged >18, fluent in English, and with normal global cognition (Montreal Cognitive Assessment, MoCA>22). The presence of ADHD diagnoses/symptoms was not required. Participants were administered the Adult Investigator Symptom Rating Scale (AISRS), the Five Facet Mindfulness Questionnaire (FFMQ) Acting with Awareness, and the DKEFS Color-Word Interference Test (CWIT). We examined the contribution of CWIT (time/sec), acting-with-awareness (AA), and their interaction in age-adjusted multiple regression predicting AISRS total score. Results Descriptives for the measures of interest were AISRS (M = 19.21, SD = 12.72), CWIT (M = 55.66, SD = 15.27), and FFMQ-AA (M = 25.10, SD = 7.17). Both CWIT and FFMQ-AA predicted AISRS when analyzed independently (B = 0.274, p = 0.14, R2 = 0.13 and B = -0.633, p < 0.001, R2 = 0.45). In the combined model, FFMQ-AA (B = -1.06, p = 0.000) but not CWIT predicted AISRS, R2 = 0.47. The interaction was not significant, p = 0.55. Conclusion AA is a powerful predictor of ADHD symptom burden: it accounts for almost half of the variance, and removes any contribution from inhibitory control. Our finding suggests that trait mindfulness has a more important role in shaping ADHD than cognition.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".