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Record W3108434790 · doi:10.1017/s0144686x20001592

Contribution of stressful life events to gambling activity in older age

2020· article· en· W3108434790 on OpenAlexaff
Roser Granero, Susana Jiménez‐Múrcia, Fernando Fernández‐Aranda, Amparo del Pino‐Gutiérrez, Teresa Mena-Moreno, Gemma Mestre‐Bach, Mónica Gómez‐Peña, Laura Moragas, Neus Aymamí, Isabelle Giroux, Marie Grall‐Bronnec, Anne Sauvaget, Ester Codina, Cristina Vintró‐Alcaraz, María Lozano‐Madrid, Marco Camozzi, Zaida Agüera, Jéssica Sánchez‐González, Gemma Casalé-Salayet, Isabel Sánchez, Hibai López-González, Isabel Baenas, José M. Menchón

Bibliographic record

VenueAgeing and Society · 2020
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité Laval
FundersEuropean Regional Development FundInstituto de Salud Carlos IIIAgència de Gestió d'Ajuts Universitaris i de RecercaGeneralitat de CatalunyaMinisterio de Economía y CompetitividadPlan Nacional sobre DrogasCentro de Investigación Biomédica en Red de Salud MentalEuropean Social FundCentres de Recerca de Catalunya
KeywordsAddictionPsychologyPopulationPathologicalMedicinePsychiatryClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Older subjects are susceptible to develop gambling problems, and researchers have attempted to assess the mechanisms underlying the gambling profile in later life. The objective of this study was to identify the main stressful life events (SLE) across the lifespan which have discriminative capacity for detecting the presence of gambling disorder (GD) in older adults. Data from two independent samples of individuals aged 50+ were analysed: N = 47 patients seeking treatment at a Pathological Gambling Outpatient Unit and N = 361 participants recruited from the general population. Sexual problems ( p < 0.001), exposure to domestic violent behaviour ( p < 0.001), severe financial problems ( p = 0.002), alcohol or drug-related problems ( p = 0.004) and extramarital sex ( p < 0.001) were related to a higher risk of GD, while getting married ( p = 0.005), moving to a new home ( p = 0.003) and moving to a new city ( p = 0.006) decreased the likelihood of disordered gambling. The accumulated number of SLE was not a predictor of the presence of GD ( p = 0.732), but patients who met clinical criteria for GD reported higher concurrence of SLE in time than control individuals ( p < 0.001). Empirical research highlights the need to include older age groups in evidence-based policies for gambling prevention, because these individuals are at high risk of onset and/or progression of behavioural addiction-related problems such as GD. The results of this study may be useful for developing reliable screening/diagnostic tools and for planning effective early intervention programmes aimed to reduce the harm related to the onset and evolution of problem gambling in older adults.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.332

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 head0.080
GPT teacher head0.376
Teacher spread0.296 · 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
Published2020
Admission routes1
Has abstractyes

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