Problem gambling severity and involvement in a self-help treatment: Comparison of problem gamblers based on recruitment method
Bibliographic record
Abstract
A better understanding of the repercussions of the means used to recommend psychological treatment could help to mitigate the low consultation rate among gamblers. This study compares the severity of the gambling problems as measured by the Problem Gambling Severity Index (PGSI) and engagement in self-adminstered treatment by problem gamblers, based on their recruitment method (advertisements vs. volunteer bank). In total, 27 gamblers were recruited by advertisements, and 31 came from a bank of volunteers, to participate in studies on gambling. All the participants took part in self-administered treatment, including a self-treatment manual and motivational telephone conversations. The results suggested that the gamblers recruited by the advertisements presented, at the time of recruitment, a significantly higher PGSI score than those recruited instead through the volunteer bank. Furthermore, the number of phases of the self-treatment manual completed, and the proportion of individuals who gave up treatment after a period of 11 weeks, did not differ significantly between the two groups. The results suggest that using different recruitment methods could work to reach those gamblers who do not actively seek help, and that this use of different methods will not affect their engagement in the treatment.RésuméUne meilleure compréhension des répercussions des moyens employés pour proposer les traitements psychologiques pourrait contribuer à pallier les faibles taux de consultation chez les joueurs. La présente étude compare la gravité des problèmes de jeu mesurée par l’Indice de gravité du jeu problématique (IGJP) et l’implication dans un traitement auto-administré chez les joueurs problématiques selon leur mode de recrutement (annonces publicitaires c. banque de volontaires). Au total, 27 joueurs sont recrutés par annonces publicitaires et 31 joueurs proviennent d’une banque de personnes volontaires à participer à des études sur les jeux de hasard et d’argent. Tous les participants prennent part à un traitement auto-administré incluant un manuel d’auto-traitement et des entretiens téléphoniques de type motivationnel. Les résultats indiquent que les joueurs recrutés par annonces publicitaires présentent, au moment de leur recrutement, un score à l’IGJP significativement plus élevé que ceux recrutés par la banque de volontaires. De plus, le nombre de phases du manuel d’auto-traitement complétées et la proportion d’individus abandonnant le traitement après une période de 11 semaines ne diffère pas significativement entre les deux groupes. Les résultats suggèrent que le recours à différentes méthodes de recrutement puisse aider à rejoindre des joueurs ne recherchant pas activement d’aide et que ceci n’affecte pas l’implication dans le traitement.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".