Belief patterns and drug use in a sample of Brazilian youth: an exploratory latent class analysis

Healy, Shannon; Martins, Silvia S.; Fidalgo, Thiago M.; Sanchez, Zila M.

doi:10.1590/1516-4446-2019-0706

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Brazilian Journal of Psychiatry

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ORIGINAL ARTICLE • Braz J Psychiatry 42 (3) • 2020 • https://doi.org/10.1590/1516-4446-2019-0706 copy

Belief patterns and drug use in a sample of Brazilian youth: an exploratory latent class analysis

Authorship SCIMAGO INSTITUTIONS RANKINGS

Objective:

Adolescent substance abuse is a public health concern worldwide, and its prevention is the subject of numerous programmatic efforts. Yet, little research exists on the structure of drug-related belief patterns in youth and their utility in preventive program planning. The aim of this study is to determine the structure of drug-related beliefs among 12-15-year-old students in Brazil using latent class analysis.

Methods:

De-identified survey data were obtained from the baseline sample (n=6,176) of a randomized controlled trial on the #Tamojunto drug use prevention program in Brazilian middle schools. Using 11 survey items assessing drug-related beliefs as indicators, four models were run and assessed for goodness-of-fit. For the best fitting model, demographic variables and substance use across latent classes were assessed.

Results:

Model fit statistics indicated that the best fit was a three-class solution, comprising a large Drug-Averse Beliefs class (80.9%), a smaller Permissive Beliefs class (12.7%), and an Inconsistent Beliefs class (6.4%). Respondents in the Permissive Beliefs and Inconsistent Beliefs classes reported greater past-year drug use, were slightly older and less likely to be female than those in the Drug-Averse Beliefs class.

Conclusions:

These results indicate that conceptualizing drug beliefs as a categorical latent variable may be useful for informing prevention. Longitudinal studies are needed to establish temporality and assess further applicability of this construct.

Prevention; school-based services; substance use; adolescent health; intervention; drug use

Belief scale item	Missingness
Using drugs can be a pleasurable activity	486 (7.87)
A young person never needs to use drugs	511 (8.27)
Using drugs is fun	485 (7.85)
There are many things riskier than doing drugs	512 (8.29)
Everyone that uses drugs will be arrested one day	540 (8.74)
Drug laws should be stronger	521 (8.44)
Drug use is one of the major problems of this country	537 (8.69)
Drugs help people experience life more intensely	551 (8.92)
Schools should teach the dangers of drugs	540 (8.74)
The police should ignore people who experiment with drugs	533 (8.63)
To experiment with drugs is to abandon control of one’s life	544 (8.81)

	n	Mean	95%CI
Age	6,176	12.6	12.6-12.7
Belief score^* * Belief score, sum of a five- (positive) or six- (negative) point scale of drug-related beliefs, further described in the Methods section.
Positive	6,176	1.08	1.04-1.11
Negative	6,176	4.40	4.30-4.50
	n	Wgt%^† † Survey-weighted proportions.	95%CI
Sex
Female	3,120	50.1	34.5-65.7
Male	3,056	49.9	34.3-65.5
City
Brasília	531	10.5	7.7-14.4
Florianópolis	840	2.4	1.8-3.2
Fortaleza	527	9.0	7.4-11.0
São Bernardo do Campo	923	5.4	3.9-7.3
São Paulo	3,035	72.1	67.5-76.3
Tubarão	320	0.6	0.4-0.8
Socioeconomic status^‡ ‡ Sociodemographic status according to the Brazilian Market Research Association’s (Associação Brasileira de Empresas de Pesquisa) scale, described in Methods section.
AB	2,628	40.4	36.5-44.3
C1	2,033	33.2	31.2-35.4
C2	1,204	20.8	18.5-23.3
DE	311	5.6	4.6-6.8
Drug use^§ § Reported use in the past year.
Alcohol	1,964	31.0	28.7-33.4
Binge drinking^\|\| \|\| Drinking five or more standard doses of alcohol on one occasion.	989	16.6	15.2-18.2
Cigarettes	237	4.0	3.3-4.9
Inhalants	510	8.2	7.5-9.0
Marijuana	153	2.6	2.0-3.2

Drug use^* * Reported use in the past year.	OR^† † Odds ratios for past-year use for each drug, from a logistic regression model controlling for group assignment, age, sex, and socioeconomic status.	95%CI	p-value
Belief score^‡ ‡ Sum score of a five- (positive) or six- (negative) point scale of drug-related beliefs, further described in the Methods section.
Positive
Alcohol	1.47	1.37-1.57	< 0.0001
Binge drinking^§ § Drinking five or more standard doses of alcohol on one occasion.	1.52	1.41-1.64	< 0.0001
Cigarettes	1.87	1.61-2.18	< 0.0001
Inhalants	1.71	1.52-1.92	< 0.0001
Marijuana	2.67	2.23-3.20	< 0.0001
Negative
Alcohol	0.93	0.90-0.97	< 0.0001
Binge drinking	0.89	0.86-0.93	< 0.0001
Cigarettes	0.87	0.82-0.93	< 0.0001
Inhalants	0.95	0.91-1.00	0.0310
Marijuana	0.85	0.79-0.92	< 0.0001

	Goodness of fit							Class size, n (%)
Class	BIC	BIC_n	AIC	VLMR LRT p-value	Entropy	Log likelihood	df	C1	C2	C3	C4	C5	C6
1	58544.4	58509.5	58471.2	-	1.000	-29224.6	11	5,764 (100.0)
2	53745.1	53672.0	53591.9	< 0.0001	0.949	-26772.9	23	5,229 (90.7)	535 (9.3)
3	52394.7	52283.5	52161.6	< 0.0001	0.832	-26045.8	35	4,662 (80.9)	734 (12.7)	368 (6.4)
4	52148.5	51999.1	51835.5	0.0810	0.723	-25870.7	47	887 (15.4)	492 (8.5)	4,047 (70.2)	339 (5.9)
5	52027.8	51840.3	51634.9	0.6004	0.663	-25758.4	59	185 (3.2)	337 (5.8)	525 (9.1)	1,315 (22.8)	3,402 (59.0)
6	52023.3	51797.7	51550.4	0.7053	0.691	-25704.2	71	169 (2.9)	624 (10.8)	486 (8.4)	333 (5.8)	495 (8.6)	3,657 (6.3)

	DAB	PB	IB	MANOVA	Overall p-value^† † Bonferroni correction.	DAB vs. PB p-value	PB vs. IB p-value	DAB vs. IB p-value
Age, mean	12.5	12.9	12.9	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	0.793	< 0.001
Sex
Male	46.9	51.6	51.8
Female	53.1	48.4	48.2	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	0.017	0.020	0.949	0.056
Socioeconomic status^‡ ‡ Sociodemographic status according to the Brazilian Market Research Association’s (Associação Brasileira de Empresas de Pesquisa) scale.
AB	42.0	45.1	43.1
C1	33.3	31.5	31.1
C2	19.6	19.6	18.0
DE	5.0	3.9	7.8	NS	0.255	0.143	0.146	0.531
Drug use^§ § Reported use in the past year.
Alcohol	28.0	55.4	36.0	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	< 0.001	0.001
Binge^\|\| \|\| Drinking five or more standard doses of alcohol on one occasion.	12.8	35.8	21.7	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	< 0.001	< 0.001
Cigarettes	2.1	14.9	5.8	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	< 0.001	< 0.001
Inhalants	6.9	18.5	7.1	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	< 0.001	0.878
Marijuana	0.7	14.7	1.9	^* * Differences were found significant using MANOVA, coefficients include Wilk’s lambda, Pillai’s trace, the Lawley-Hotelling trace, and Roy’s largest root.	< 0.001	< 0.001	< 0.001	0.009

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[1] Correspondence: Thiago M. Fidalgo, Universidade Federal de São Paulo, Departamento de Psiquiatria, Rua Major Maragliano, 241, Vila Mariana, CEP 04017-030, São Paulo, SP, Brazil. E-mail: marquesfidalgo@yahoo.com.br