Exploring the Relationships Between Problem Gambling and ADHD: A Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: At present, there are inconsistencies in the literature pertaining to the association between ADHD and problem gambling. This study utilized meta-analytic techniques to clarify the association between symptoms of problem gambling and symptoms of ADHD. Method: Several meta-analyses were conducted using a random effects model. PsycINFO, PubMed, ProQuest Dissertations & Theses, and Google Scholar were searched for relevant studies. Results: The weighted mean correlation between ADHD symptomology and gambling severity was r = .17, 95% confidence interval (CI) = [0.12, 0.22], p < .001. Mean age of the sample was the only moderator to approach significance, with greater age being linked to a stronger relationship between symptoms of ADHD and gambling severity. Conclusion: Clinicians needs to be cognizant of the greater risk of ADHD symptoms when working with problem gamblers and vice versa.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it