Developing a Best Practices Guide for the Prevention of Problem Gambling Among Older Adults
Bibliographic record
Abstract
The purpose of this research and development project was to describe the complete gambling experience and to develop best practices for the prevention of problem gambling among older adults (55 years and over) in Ontario. The challenging task of developing best practices involved integrated research and development, as well as knowledge translation and exchange (KTE) throughout the project. We developed a large, multi-organizational, multidisciplinary research team, as well as prevention and treatment work groups comprising investigators, KTE personnel, knowledge users, and service providers from key stakeholder organizations. Research dealing specifically with older adults is scarce; thus, research from other age groups was also drawn upon for this report. We incorporated a variety of types of evidence, including empirical, theoretical, expert opinion, practice-based, and normative. To obtain feedback ahead of finalizing the best practices, we disseminated preliminary best practices to key informants and other knowledge users and service providers. This feedback was incorporated into the current document. This paper presents the first set of evidence-based best practices for the prevention of problem gambling among older adults, including evidence sources, commentary, and references. We hope that these best practices help enhance prevention programs, services, and practices. In addition, we hope that this study prompts future research that examines areas that are currently insufficiently researched and helps provoke a dialogue that will lead to a broader knowledge base to guide prevention policies and practices directed at this growing segment of the population.RésuméCe projet de recherche et développement avait comme objectif de décrire l’expérience de jeu complète et de concevoir des pratiques exemplaires pour la prévention du jeu compulsif chez les adultes âgés de 55 ans et plus, en Ontario. La difficile tâche de développer des pratiques exemplaires comprenait la recherche et le développement intégrés et l’application et le transfert de connaissances tout au long du projet. Nous avons créé une grande équipe de recherche multidisciplinaire et multiorganisationnelle, ainsi que des groupes de travail sur la prévention et le traitement, composés de chercheurs, de personnel pour le transfert de connaissances, d’utilisateurs de connaissances et de fournisseurs de services provenant des principales organisations participantes. Les recherches portant spécifiquement sur les personnes plus âgées sont rares, ce qui explique le recours à la recherche sur d’autres groupes d’âge pour ce rapport. Nous avons incorporé divers types de données probantes, notamment des preuves empiriques et théoriques, des opinions d’experts et des preuves fondées sur la pratique et des faits. Pour obtenir des commentaires avant la finalisation des pratiques exemplaires, on a transmis les pratiques préliminaires aux informateurs clés et aux autres utilisateurs des connaissances et fournisseurs de services. Leur rétroaction a été intégrée dans le document actuel. Cet article présente la première série de pratiques exemplaires fondées sur des données probantes pour la prévention du jeu problématique chez les adultes en âge avancé, y compris les sources de preuves, les commentaires et les références. Nous souhaitons qu’elles puissent aider à améliorer les programmes, les services et les moyens de prévention. De plus, nous avons bon espoir que cette étude influencera les futures recherches pour l’examen de domaines actuellement peu étudiés et ouvrir un dialogue qui conduira à une base de connaissances plus large afin d’orienter les politiques et les pratiques de prévention destinées à ce segment croissant de la population.
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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 | 0.070 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".