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Record W2087626170 · doi:10.1037//0022-006x.69.1.50

Motivational enhancement and self-help treatments for problem gambling.

2001· article· en· W2087626170 on OpenAlexaff
David C. Hodgins, Shawn R. Currie, Nady el‐Guebaly

Bibliographic record

VenueJournal of Consulting and Clinical Psychology · 2001
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsFoothills Medical Centre
Fundersnot available
KeywordsWorkbookPsychologyRandomized controlled trialIntervention (counseling)Clinical psychologySelf-controlPsychiatryPsychotherapistMedicine

Abstract

fetched live from OpenAlex

Two brief treatments for problem gambling were compared with a waiting-list control in a randomized trial. Eighty-four percent of participants (N = 102) reported a significant reduction in gambling over a 12-month follow-up period. Participants who received a motivational enhancement telephone intervention and a self-help workbook in the mail, but not those who received the workbook only, had better outcomes than participants in a 1-month waiting-list control. Participants who received the motivational interview and workbook showed better outcomes than those receiving the workbook only at 3- and 6-month follow-ups. At the 12-month follow-up, the advantage of the motivational interview and workbook condition was found only for participants with less severe gambling problems. Overall, these results support the effectiveness of a brief telephone and mail-based treatment for problem gambling.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.224
GPT teacher head0.520
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations265
Published2001
Admission routes1
Has abstractyes

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