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Record W2896543248 · doi:10.4309/jgi.2018.39.5

Developing a Best Practices Guide for the Prevention of Problem Gambling Among Older Adults

2018· article· en· W2896543248 on OpenAlexaffvenueabout
Nigel E. Turner, Jamie Wiebe, Peter Ferentzy, N. Leroy Kauffman, Salaha Zaheer, Trudy Smit Quosai, Travis Sztainert, Robert Murray, Hayley A. Hamilton, Sherald Sanchez, Flora I. Matheson, John McCready, Robert E. Mann

Bibliographic record

VenueJournal of Gambling Issues · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsSt. Michael's HospitalGreoGovernment of OntarioUniversity of TorontoOntario Brain InstituteCentre for Addiction and Mental Health
Fundersnot available
KeywordsBest practiceKnowledge translationPsychologyStakeholderPublic relationsNormativeService (business)PopulationService providerMedical educationKnowledge managementPolitical scienceBusinessMedicineMarketingComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.335
GPT teacher head0.513
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2018
Admission routes3
Has abstractyes

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