The Development of an Internet-Based Treatment for Problem Gamblers and Concerned Significant Others: A Pilot Randomized Controlled Trial

Nilsson, Anders; Magnusson, Kristoffer; Carlbring, Per; Andersson, Gerhard; Gumpert, Clara Hellner

doi:10.1007/s10899-017-9704-4

Cited by 35 publications

(46 citation statements)

References 66 publications

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“…For CSOs, the differences in outcomes were surprisingly small, considering that the CBT condition for CSOs was a control group. This differs from the results of the pilot trial, as well as other trials offering support to CSOs …”

Section: Discussioncontrasting

confidence: 91%

Behavioral couples therapy versus cognitive behavioral therapy for problem gambling: a randomized controlled trial

et al. 2020

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Background and aims There is evidence that cognitive behavioral therapy (CBT) is effective for treating problem gambling (PG). Some research points to the possible benefits of involving concerned significant others (CSOs) in treatment. This study compared the efficacy of behavioral couples therapy (BCT) and CBT for both the gambler and the CSO. Design Two parallel‐group randomized controlled study comparing two different internet‐based treatments for PG. Follow‐up measures were conducted at treatment finish, and at 3‐, 6‐ and 12‐month post‐treatment. Setting Stockholm, Sweden. Participants A total of 136 problem gamblers and 136 CSOs were included in the study: 68 gamblers and 68 CSOs for each treatment condition. The gamblers were on average 35.6 years old and 18.4% were female. CSOs were on average 45.3 years old and 75.7% were women. Interventions A treatment based on BCT was compared with a CBT intervention. Both treatments were internet‐based, with 10 therapist‐guided self‐help modules accompanied by weekly telephone and e‐mail support from a therapist. CSOs were given treatment in the BCT condition, but not in the CBT condition. Measurements The primary outcome measures were time‐line follow‐back for gambling (TLFB‐G) and the NORC Diagnostic Screen for Gambling Problems (NODS) for problem gamblers, corresponding to DSM‐IV criteria for pathological gambling. Secondary outcomes measures were the Patient Health Questionnaire‐9 (PHQ‐9), the Generalized Anxiety Disorder seven‐item scale (GAD‐7), the Relation Assessment Scale Generic (RAS‐G), the Alcohol Use Disorders Identification Test (AUDIT), the Inventory of Consequences of Gambling for the Gambler and CSO (ICS) and adherence to treatment for both the problem gambler and the CSO. Findings The outcomes of both gambler groups improved, and differences between the groups were not statistically significant: TLFB‐G: multiplicative effect = 1.13, 95% confidence interval (CI) = 0.30;4.31); NODS: multiplicative effect = 0.80, 95%, 95% CI = 0.24;2.36. BCT gamblers began treatment to a higher proportion than CBT gamblers: P = 0.002. Conclusions Differences in the efficacy of internet‐based behavioral couples therapy and cognitive behavioral therapy for treatment of problem gambling were not significant, but more gamblers commenced treatment in the behavioral couples therapy group.

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Section: Discussioncontrasting

confidence: 91%

Behavioral couples therapy versus cognitive behavioral therapy for problem gambling: a randomized controlled trial

et al. 2020

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“…It is reasonable to assume that many partners have shared finances, which increases their insight into each other’s financial situation (Gunnarsson and Wahlund 1997; Heimdal and Houseknecht 2003). Moreover, the qualitative assessment conducted as part of the pilot testing of the intervention evaluated in the RCT revealed that some gamblers, especially in parent–child dyads, appear to have been pressured into participation by their CSO (Nilsson et al 2018). This could affect the gambler’s willingness to reveal details about his or her gambling.…”

Section: Discussionmentioning

confidence: 99%

“…The treatments were based on cognitive behavioral therapy, and they were internet-based, with therapist support being provided via email and telephone (c.f., Carlbring and Smit 2008). Data are also included from a pilot study (Nilsson et al 2018) conducted prior to the randomized controlled trial (RCT). The pilot and the RCT data were pooled, since the recruitment and screening processes were identical, and recruitment into the RCT followed immediately after the completion of the pilot study.…”

Section: Methodsmentioning

confidence: 99%

Level of Agreement Between Problem Gamblers’ and Collaterals’ Reports: A Bayesian Random-Effects Two-Part Model

et al. 2019

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This study investigates the level of agreement between problem gamblers and their concerned significant others (CSOs) regarding the amount of money lost when gambling. Reported losses were analyzed from 266 participants (133 dyads) seeking treatment, which included different types of CSO–gambler dyads. The intraclass correlation coefficients (ICCs) concerning the money lost when gambling during the last 30 days were calculated based on the timeline followback. In order to model reports that were highly skewed and included zeros, a two-part generalized linear mixed-effects model was used. The results were compared from models assuming either a Gaussian, two-part gamma, or two-part lognormal response distribution. Overall, the results indicated a fair level of agreement, ICC = .57, 95% CI (.48, .64), between the gamblers and their CSOs. The partner CSOs tended to exhibit better agreement than the parent CSOs with regard to the amount of money lost, ICCdiff = .20, 95% CI (.03, .39). The difference became smaller and inconclusive when reports of no losses (zeros) were included, ICCdiff = .16, 95% CI (− .05, .36). A small simulation investigation indicated that the two-part model worked well under assumptions related to this study, and further, that calculating the ICCs under normal assumptions led to incorrect conclusions regarding the level of agreement for skewed reports (such as gambling losses). For gambling losses, the normal assumption is unlikely to hold and ICCs based on this assumption are likely to be highly unreliable.

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“…Les résultats encourageants ont montré des tailles 6 d'effets importantes en fin de traitement avec un maintien à 6, 18 et 36 mois. Depuis, quelques études ont pu confirmer l'efficacité de la TCC à distance [16][17][18]. En 2016, Luquiens et al [19] ont utilisé les données de comptes de joueurs de poker pour évaluer l'efficacité de trois modalités de psychothérapie à distance (retour personnalisé [ou feedback], TCC personnalisée avec thérapeute, TCC sans thérapeute).…”

Section: Big Data Et Médecine Préventiveunclassified

La santé à l’ère du numérique

Santiago

Carré²,

Miranda³

et al. 2019

Med Sci (Paris)

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Les technologies de l’information et de la communication ont profondément marqué le champ de la santé. De nouvelles pratiques médicales utilisant ces technologies tentent de promouvoir une meilleure égalité d’accès aux soins, en particulier dans le champ de la santé mentale et des addictions où le recours aux professionnels de santé demeure faible. L’addiction aux jeux de hasard et d’argent en ligne, que nous désignerons sous le terme de jeu problématique, semble représenter un modèle pertinent de mesures de prévention et de soin fondé sur l’exploitation des données numériques issues du Big data et sur l’utilisation des nouvelles technologies. Ens effet, les données issues des comptes des joueurs offrent la possibilité d’une lecture directe de leur comportement de jeu. Parallèlement, le recours à l’internet offre un cadre de soin auquel les joueurs en ligne pourraient être particulièrement sensibles.

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The Development of an Internet-Based Treatment for Problem Gamblers and Concerned Significant Others: A Pilot Randomized Controlled Trial

Cited by 35 publications

References 66 publications

Behavioral couples therapy versus cognitive behavioral therapy for problem gambling: a randomized controlled trial

Behavioral couples therapy versus cognitive behavioral therapy for problem gambling: a randomized controlled trial

Level of Agreement Between Problem Gamblers’ and Collaterals’ Reports: A Bayesian Random-Effects Two-Part Model

La santé à l’ère du numérique

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