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Adolescent gambling behaviour, a single latent construct and indicators of risk: findings from a national survey of New Zealand high school students

View Article: PubMed Central - PubMed

ABSTRACT

This study explores underlying latent construct/s of gambling behaviour, and identifies indicators of “unhealthy gambling”. Data were collected from Youth’07 a nationally representative sample of New Zealand secondary school students (N = 9107). Exploratory factor analyses, item-response theory analyses, multiple indicators-multiple causes, and differential item functioning analyses were used to assess dimensionality of gambling behaviour, underlying factors, and indicators of unhealthy gambling. A single underlying continuum of gambling behaviour was identified. Gambling frequency and ‘gambling because I can’t stop’ were most strongly associated with unhealthy gambling. Gambling to ‘feel better about myself’ and to ‘forget about things’ provided the most precise discriminants of unhealthy gambling. Multivariable analyses found that school connectedness was associated with lower levels of unhealthy gambling.

No MeSH data available.


MIMIC model of unhealthy gambling behaviour. Relates to students who have gambled in the past 12 months (N = 2234)
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Fig2: MIMIC model of unhealthy gambling behaviour. Relates to students who have gambled in the past 12 months (N = 2234)

Mentions: MIMIC modelling was carried out to determine if there were significant direct effects between demographic variables (i.e. age, sex, and ethnicity) and the gambling items, and whether any of the demographic subgroups were at increased or decreased risk of unhealthy gambling behaviours (see Fig. 2). Differential Item Functioning (DIF) demonstrated item equivalence for seven gambling items (gambling “to relax”, gambling “to feel better”, gambling “to forget”, gambling “because can’t stop”, frequency of gambling, money spent gambling, and time spent gambling) across the age, sex and ethnic groups of students. The MIMIC model provided a good fit for the data (RMSEA = 0.030, CFI = 0.979, TLI = 0.973) and ‘unhealthy gambling’ behaviour was shown to vary across each of the investigated demographic variables. Higher levels of ‘unhealthy gambling’ behaviour were associated with being younger, male, and being an ethnic minority. Fig. 2


Adolescent gambling behaviour, a single latent construct and indicators of risk: findings from a national survey of New Zealand high school students
MIMIC model of unhealthy gambling behaviour. Relates to students who have gambled in the past 12 months (N = 2234)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4998168&req=5

Fig2: MIMIC model of unhealthy gambling behaviour. Relates to students who have gambled in the past 12 months (N = 2234)
Mentions: MIMIC modelling was carried out to determine if there were significant direct effects between demographic variables (i.e. age, sex, and ethnicity) and the gambling items, and whether any of the demographic subgroups were at increased or decreased risk of unhealthy gambling behaviours (see Fig. 2). Differential Item Functioning (DIF) demonstrated item equivalence for seven gambling items (gambling “to relax”, gambling “to feel better”, gambling “to forget”, gambling “because can’t stop”, frequency of gambling, money spent gambling, and time spent gambling) across the age, sex and ethnic groups of students. The MIMIC model provided a good fit for the data (RMSEA = 0.030, CFI = 0.979, TLI = 0.973) and ‘unhealthy gambling’ behaviour was shown to vary across each of the investigated demographic variables. Higher levels of ‘unhealthy gambling’ behaviour were associated with being younger, male, and being an ethnic minority. Fig. 2

View Article: PubMed Central - PubMed

ABSTRACT

This study explores underlying latent construct/s of gambling behaviour, and identifies indicators of “unhealthy gambling”. Data were collected from Youth’07 a nationally representative sample of New Zealand secondary school students (N = 9107). Exploratory factor analyses, item-response theory analyses, multiple indicators-multiple causes, and differential item functioning analyses were used to assess dimensionality of gambling behaviour, underlying factors, and indicators of unhealthy gambling. A single underlying continuum of gambling behaviour was identified. Gambling frequency and ‘gambling because I can’t stop’ were most strongly associated with unhealthy gambling. Gambling to ‘feel better about myself’ and to ‘forget about things’ provided the most precise discriminants of unhealthy gambling. Multivariable analyses found that school connectedness was associated with lower levels of unhealthy gambling.

No MeSH data available.