Pilot Study of the Cognitive–Functional Intervention for Adults (Cog-Fun A): A Metacognitive–Functional Tool for Adults With Attention Deficit Hyperactivity Disorder
Bibliographic record
Abstract
IMPORTANCE: Adults with attention deficit hyperactivity disorder (ADHD) often experience chronic challenges in their life roles. There is a need for evidence-based occupational therapy interventions to help enhance their functioning. OBJECTIVE: To determine the preliminary effectiveness of the Cognitive-Functional Intervention for Adults (Cog-Fun A), a metacognitive-functional occupational therapy tool for the improvement of occupational performance (OP) and quality of life (QoL) in adults with ADHD. DESIGN: One-group pretest-posttest design with a 3-mo follow-up. SETTING: Community setting in Jerusalem, Israel. PARTICIPANTS: Fourteen adults, ages 18-60 yr, with a valid diagnosis of ADHD and an indication of executive function (EF) impairment. INTERVENTION: Participants received 15 1-hr weekly sessions that addressed self-awareness of strengths and challenges through education and guided discovery as well as strategy acquisition and implementation within a context of occupational goal attainment. OUTCOMES AND MEASURES: The Behavioral Rating Inventory of Executive Function-Adult version, an adult ADHD QoL measure, the Canadian Occupational Performance Measure, and the Self-Regulation Skills Interview were administered. RESULTS: Twelve participants completed the intervention. Posttreatment scores revealed statistically significant improvements in EF, awareness, OP, and QoL. Gains in QoL showed a modest reduction at the 3-mo follow-up. CONCLUSIONS AND RELEVANCE: The Cog-Fun A is a promising intervention for improving OP and QoL among adults with ADHD and should be investigated further. What This Article Adds: The Cog-Fun A offers an effective nonpharmacological, metacognitive-functional, occupation-centered treatment option for adults with ADHD.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".