The role of medication in the treatment of pathological gambling: Bridging the gap between research and practice
Bibliographic record
Abstract
After reviewing the literature on the pharmacotherapy of pathological gambling, the author discusses treatment strategies and areas for future research. The clearest indication for medicating the pathological gambler is for the treatment of comorbid disorders, primarily depression, bipolar disorder, and attention deficit hyperactivity disorder. However, there are difficulties in diagnosing the dually disordered gambler. Other current pharmacological approaches involve the use of medication to treat specific symptoms, traits, or symptom clusters; to make negative affects more tolerable; and to reduce cravings. Future approaches will be directed at subgroups of gamblers. This may include genetic profiling, paired with recognition of neurotransmitter deficits, and the identification of clinical syndromes and subtypes. The author also discusses the kindling hypothesis as it may pertain to pathological gambling. The presence of kindling would make a strong case for earlier and more aggressive use of medication and for long-term maintenance to prevent relapse.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".