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Record W2898272712 · doi:10.4309/jgi.2018.39.6

Best Practices for the Treatment of Older Adult Problem Gamblers

2018· article· en· W2898272712 on OpenAlexaffvenueabout
W. J. Skinner, Nina Littman-Sharp, Jane Leslie, Peter Ferentzy, Salaha Zaheer, Trudy Smit Quosai, Travis Sztainert, Robert E. Mann, John McCready

Bibliographic record

VenueJournal of Gambling Issues · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of TorontoGreoCentre for Addiction and Mental Health
Fundersnot available
KeywordsBest practicePsychologyAnticipation (artificial intelligence)Intervention (counseling)PopulationSet (abstract data type)CognitionPsychological interventionGerontologyMedicinePsychiatryPolitical science

Abstract

fetched live from OpenAlex

Whereas the proportion of older adults who experience gambling problems appears relatively small, factors such as cognitive changes with age, social isolation and maintaining fixed incomes can make older adults particularly susceptible to gambling problems, increasing the severity of the consequences they may experience. Relatively few resources are available that are directed specifically to older adults with gambling problems. This report identifies, based on the knowledge and evidence currently available, Best Practices for treating gambling problems among older adults intended for practitioners, patients, families, policy makers and others concerned with this population. A team of gambling researchers and experienced clinicians first identified overarching conceptual frameworks to guide the work. The researchers then shaped a set of Best Practices that was reviewed by a working group developing Best Practices for preventing gambling problems among older adults. Based on their feedback, the authors created a final set of Best Practices. This process was informed at all stages by a systematic review of the literature, evidence from a recent population survey of gambling among Ontario older adults, and ongoing review by practice experts. These guidelines focus on five areas: (1) person-centred and family-focused care, (2) screening and assessment, (3) secondary prevention and early intervention, (4) tertiary prevention and specialized treatment, and (5) ongoing support and recovery resources. Limitations include the paucity of studies specifically on gambling and older adults. We offer these as the most current clinical guidelines for those clinicians and researchers working with older adults, in anticipation of evolving Best Practices as new evidence and consequent greater knowledge become available.RésuméBien que la proportion de personnes âgées ayant des problèmes de jeu semble relativement faible, des facteurs tels que les changements cognitifs avec l’âge, l’isolement social et des revenus fixes peuvent rendre les adultes plus vulnérables aux problèmes de jeu, ce qui augmente la gravité des conséquences. Il existe relativement peu de ressources disponibles destinées spécifiquement aux personnes âgées ayant des problèmes de jeu. Selon les connaissances et les données probantes actuellement disponibles, ce rapport fait l’inventaire des meilleures pratiques pour traiter les problèmes de jeu chez les personnes âgées, pratiques qui sont destinées aux praticiens, aux patients, aux familles, aux décideurs et aux autres personnes concernées par cette population. Une équipe de chercheurs sur le jeu et de cliniciens chevronnés a d’abord établi les cadres conceptuels généraux pour guider le travail. Ensuite, un ensemble de pratiques exemplaires a été constitué et examiné par un groupe de travail chargé de mettre au point les meilleures pratiques pour prévenir les problèmes de jeu chez les personnes âgées. Un ensemble de meilleures pratiques a été retenu en tenant compte de leurs commentaires. Toutes les étapes du processus ont été soutenues par une revue systématique de la littérature, des preuves tirées d’une enquête récente sur la population des personnes âgées en Ontario et un examen continu effectué par des experts praticiens. Les directives portent sur cinq domaines: (1) les soins centrés sur la personne et la famille, (2) le dépistage et l’évaluation, (3) la prévention secondaire et l’intervention précoce, (4) la prévention tertiaire et le traitement spécialisé, (5) ainsi que les ressources permanentes pour le soutien et le rétablissement. La rareté des études portant spécifiquement sur le jeu et les personnes plus âgées a limité cette analyse. Nous offrons actuellement les meilleures lignes directrices cliniques aux personnes qui travaillent avec des personnes âgées, en gardant en vue l’évolution des meilleures pratiques au gré de nouvelles preuves et connaissances.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.362
GPT teacher head0.508
Teacher spread0.147 · 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 designNot applicable
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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