Core Competencies for Disordered Gambling Counsellors: A Modified Delphi Study
Bibliographic record
Abstract
Counselling for disordered gambling has emerged as a unique professional field. Research and literature on treatment approaches and best practices has burgeoned over the past 30 years. This has included the development of journals, field-specific conferences, and professional training programs specifically dedicated to understanding and treating gambling problems. Mental health professionals are now expected to master field specific knowledge and undergo supervision prior to engaging in problem gambling counselling. In this paper, we share the results of a modified Delphi study in which 45 experts reached agreement on core competencies for problem gambling treatment providers. A total of 166 core competencies were endorsed as high agreement items. The authors share implications and the potential usefulness of core competencies for problem gambling counsellor professional preparation, workforce development, and quality of care.RésuméLe counseling consacré au jeu pathologique est devenu un domaine professionnel à part entière. Depuis une trentaine d’années, les travaux de recherche sur les approches et les pratiques exemplaires en matière de traitement ont connu un véritable essor. Ainsi, on a vu apparaître des revues, des conférences spécialisées et des programmes de formation dédiés à l’analyse des problèmes de jeu et à leur traitement. Aujourd’hui, les professionnels de la santé mentale intéressés par ce domaine doivent acquérir des connaissances précises sur le sujet et travailler sous la supervision d’un spécialiste avant de s’y consacrer. Cet article présente les résultats d’une enquête Delphi modifiée à laquelle ont participé 45 spécialistes qui se sont mis d’accord sur les compétences de base à exiger des fournisseurs de traitement. Au total, 166 compétences font l’objet d’un large consensus. Les auteurs discutent des implications découlant de l’enquête, de l’utilité éventuelle des compétences de base en matière de formation professionnelle, de perfectionnement de la main-d’œuvre et de qualité des soins.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".