The Experience of Couples in the Process of Treatment of Pathological Gambling: Couple vs. Individual Therapy
Bibliographic record
Abstract
Context. Couple treatment for pathological gambling is an innovative strategy. There are some results supporting its potential effectiveness, but little is known about the subjective experiences of the participants. Objective. The aim of this article is to document the experiences of gamblers and their partners participating in one of two treatments, namely individual or couple. Method. In a study aiming to evaluate the efficacy of the Integrative Couple Treatment for Pathological Gambling (ICT-PG), couples who were entering specialized treatment for the addiction of one member who was a pathological gambler were randomly assigned to individual or ICT-PG. Nine months after their admission to treatment, gamblers and partners (n=21 couples; n=13 ICT-PG; n=8 individual treatment) were interviewed in semi-structured interviews. A sequenced thematization method was used to extract the major themes. Results. This study highlighted five major themes in the therapeutic process noted by the gamblers and their partners mainly after the couple treatment but also partly through the individual therapy. These were: 1) the gamblers’ anxiety about having to reveal their gambling problems in couple therapy; 2) the wish to develop a mutually beneficial understanding of gambling and its effects on the partners in the two types of treatments; 3) the transformation of negative attributions through a more effective intra-couple communication fostered by the couple therapy; 4) the partners’ contribution to changes in gambling behaviour and prevention of relapses, which were both better supported in couple therapy; and 5) the interpersonal nature of gambling and its connections with the couples’ relationship. However, gamblers who were in individual treatment were more likely to mention that their partners’ involvement was not necessary. Participants likewise made a few recommendations about the conditions underlying the choice of one treatment method or the other. Discussion. Participants reported satisfaction with both treatment models, but their experiences was more positive in couple treatment. Complementary benefits emerged from each form of treatment, which points to future treatments involving both types. Future research should explore both the couple processes associated with attempts to stop pathological gambling and the various ways of involving partners in the gamblers’ treatment.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".