| Title |
Subtyping Non-treatment-seeking Problem Gamblers Using the Pathways Model
|
|---|---|
| Published in |
Journal of Gambling Studies, December 2016
|
| DOI | 10.1007/s10899-016-9658-y |
| Pubmed ID | |
| Authors |
Miea Moon, Jamey J. Lister, Aleks Milosevic, David M. Ledgerwood |
| Abstract |
This study examined whether distinct subgroups could be identified among a sample of non-treatment-seeking problem and pathological/disordered gamblers (PG) using Blaszczynski and Nower's (Addiction 97:487-499, 2002) pathways model (N = 150, 50% female). We examined coping motives for gambling, childhood trauma, boredom proneness, risk-taking, impulsivity, attention-deficit/hyperactivity disorder (ADHD), and antisocial personality disorder as defining variables in a hierarchical cluster analysis to identify subgroups. Subgroup differences in gambling, psychiatric, and demographic variables were also assessed to establish concurrent validity. Consistent with the pathways model, our analyses identified three gambling subgroups: (1) behaviorally conditioned (BC), (2) emotionally vulnerable (EV), and (3) antisocial-impulsivist (AI) gamblers. BC gamblers (n = 47) reported the lowest levels of lifetime depression, anxiety, gambling severity, and interest in problem gambling treatment. EV gamblers (n = 53) reported the highest levels of childhood trauma, motivation to gamble to cope with negative emotions, gambling-related suicidal ideation, and family history of gambling problems. AI gamblers (n = 50) reported the highest levels of antisocial personality disorder and ADHD symptoms, as well as higher rates of impulsivity and risk-taking than EV gamblers. The findings provide evidence for the validity of the pathways model as a framework for conceptualizing PG subtypes in a non-treatment-seeking sample, and underscore the importance of tailoring treatment approaches to meet the respective clinical needs of these subtypes. |
Mendeley readers
The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | <1% |
| Unknown | 113 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 19 | 17% |
| Student > Master | 18 | 16% |
| Student > Ph. D. Student | 16 | 14% |
| Student > Doctoral Student | 10 | 9% |
| Professor | 3 | 3% |
| Other | 14 | 12% |
| Unknown | 34 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 45 | 39% |
| Social Sciences | 11 | 10% |
| Medicine and Dentistry | 7 | 6% |
| Business, Management and Accounting | 4 | 4% |
| Engineering | 3 | 3% |
| Other | 6 | 5% |
| Unknown | 38 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2018.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Journal of Gambling Studies
#692
of 989 outputs
Outputs of similar age
#265,492
of 420,078 outputs
Outputs of similar age from Journal of Gambling Studies
#14
of 17 outputs
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