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Journal : Small 10899 Dispatch : 4-4-2012 Pages : 14 Article No. : 9303 h LE h TYPESET MS Code : JOGS637 h4 CP h4 DISK J Gambl Stud Author Proof 248 friends’ tobacco use, and showed a trend toward an association with their friends’ 249 gambling. Within-modality relations thus appear to be stronger than between-modality 250 relations, between participants and their friends. Finally, many studies have observed 251 that alcohol and tobacco use tend to co-occur in individuals. The current data replicate 252 this finding, both for the individual and among the friends’ behaviors (Table 1). 253 Social Density of Gambling, Alcohol and Tobacco Use Among Family Members 254 Findings relating self-behavior to parents’ and siblings’ behaviors in gambling, alcohol and 255 tobacco use are depicted in Table 2. The clear patterns of social density observed among 256 friends were not seen as strongly among family members. Participants’ gambling severity 257 was significantly associated with fathers’ frequency of gambling (r=.30) but was not 258 associated with fathers’ gambling expenditure. No significant relationships were found 259 between participants’ gambling severity and the gambling variables for mothers, a parental 260 composite, or sibling composite. For alcohol use, a significant correlation was observed 261 between participants’ AUDIT scores and Mothers’ alcohol consumption, but not other 262 significant relationships emerged from the alcohol use of parents or siblings. In the domain 263 of tobacco use, no significant associations were observed between participants and any 264 biological relatives. 265 Discussion 266 The present study investigated the relationship between individual-level PG, alcohol and 267 tobacco use, and the density of gambling behavior in participants’ social networks. 268 With regard to gambling, consistent with our hypothesis, participants’ gambling severity 269 was significantly and positively associated with both frequency of gambling and 270 monetary expenditure on gambling within a person’s immediate non-family social 271 network. Consistent with prior research (e.g., Oei and Raylu 2004), participants’ 272 gambling severity was significantly correlated with fathers’ gambling frequency; 273 whereas participants gambling severity was not associated with either mothers’ or 274 siblings’ gambling practices. Overall, participants’ friends displayed a significant rela- 275 tionship with their current gambling behaviors, which may support the notion proposed 276 by Gupta and Derevensky (1997) that parents act as a dominant influence for the 277 development of gambling behaviors, which may occur in adolescence, whereas friends 278 aid in the maintenance of gambling activity through adolescence and adulthood. It is Table 2 Correlations between participants’ DIGS scores and the frequency of gambling, gambling expenditure, alcohol use, and tobacco use of parents and siblings Relationship Frequency N Expenditure N Alcohol N Tobacco N Parents Father .30* 71 .16 68 .05 72 .21 63 Mother -.06 78 -.04 80 .32** 78 .15 72 UNCORRECTED PROOF Composite .12 90 .10 91 .06 91 .17 84 Siblings Composite .06 100 .11 101 .04 101 .02 93 * p\.05; ** p\.01 123
J Gambl Stud Journal : Small 10899 Dispatch : 4-4-2012 Pages : 14 Article No. : 9303 h LE h TYPESET MS Code : JOGS637 h4 CP h4 DISK Author Proof 279 possible that a similar study using a younger cohort would have revealed greater rel- 280 ative associations with family activities. The current findings related to alcohol and 281 tobacco use provide further support for previous research showing the importance of 282 peers in current alcohol consumption and tobacco use, in a sample that uniquely 283 combines investigation of these potentially addictive behaviors with gambling behav- 284 iors. This too is comparable to earlier studies that highlight the more significant impact 285 of peers over both parents and siblings. 286 Collectively, the gambling, alcohol, and tobacco findings create a relatively cohesive 287 view of the importance of nonbiological social relationships and the apparent reci- 288 procity between a person’s gambling, drinking, and smoking, and the prevalence of 289 those behaviors in his or her social network. Importantly, however, these are cross- 290 sectional data, making it difficult to assess whether these relationships reflect causal 291 links or consequences of self-selection. The presence of more frequent and heavy 292 gamblers may increase an individual’s gambling by providing partners and opportunities 293 to gamble, or may be observed because pathological gamblers seek out individuals with 294 similar interests. It is plausible that both causal chains are in operation, and that social 295 factors are recursive motivational factors. For example, an individual whose gambling is 296 escalating is increasingly likely to seek out and meet other heavy gamblers, who in turn 297 may become partners and provide opportunities, thus reflecting both causal and con- 298 sequential roles. 299 Strengths and Limitations 300 These findings should be considered in light of the study’s strengths and limitations. Study 301 strengths include the assessment of each participant’s level of gambling pathology using a 302 gold-standard clinical interview and the use of a racially diverse community sample. 303 However, one limitation that bears consideration is that the social network data were not 304 directly retrieved from the network members, but were supplied by the participants in this 305 preliminary study. Although the participants had high confidence in their response accu- 306 racy, the potential for error is present when estimating the behaviors of others. Perception 307 may systematically be skewed in the direction of a person’s behavior, with low severity 308 individuals underestimating behavior and high severity individuals overestimating 309 behavior. As such, these finding should be interpreted cautiously and not be considered 310 definitive. This issue itself is worthy of study. For example, future studies could examine 311 estimated behavior and self-reported behavior among cohorts of individuals to empirically 312 determine the extent to which a disconnect exists. The most rigorous application of this 313 approach is termed sociocentric SNA, and includes comprehensive assessment of all 314 members of a bounded population (both for the individual and their estimates of other 315 individual’s behaviors), permitting both objectivity and analysis of the discrepancy 316 between self-reports and other reports (e.g., Clifton et al. 2009), and would directly address 317 this issue. Further study of the social density of PG using diverse methodologies is clearly 318 warranted. 319 A last consideration is that participants were asked to provide information only for 320 living parents and siblings. However, if parents are primarily responsible for their 321 offspring’s acquisition of gambling behaviors early in life, as Gupta and Derevensky 322 (1997) suggest, even parents who are currently deceased could have potentially had a 323 significant impact on participants’ current gambling behaviors. Furthermore, the role of 324 genetics in PG should not be overlooked. Although research in this area is in its 325 infancy, a recent review on the topic indicated that genetic factors may explain between UNCORRECTED PROOF 123
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