Diseño y validación de una escala de intención de consumo de cannabis (CUIQ) para adolescentes

  1. Daniel Lloret Irles 1
  2. Ramón Morell-Gomis 1
  3. Ana Laguía 2
  4. Juan A. Moriano 2
  1. 1 Universidad Miguel Hernández de Elche
    info

    Universidad Miguel Hernández de Elche

    Elche, España

    ROR https://ror.org/01azzms13

  2. 2 Universidad Nacional de Educación a Distancia
    info

    Universidad Nacional de Educación a Distancia

    Madrid, España

    ROR https://ror.org/02msb5n36

Zeitschrift:
Adicciones: Revista de socidrogalcohol

ISSN: 0214-4840

Datum der Publikation: 2018

Ausgabe: 30

Nummer: 1

Seiten: 54-65

Art: Artikel

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Andere Publikationen in: Adicciones: Revista de socidrogalcohol

Zusammenfassung

In Spain, one in four 14 to 18-year-old adolescents has used cannabis during the last twelve months. Demand for treatment has increased in European countries. These facts have prompted the development of preventive interventions that require screening tools in order to identify the vulnerable population and to properly asses the efficacy of such interventions. The Theory of Planned Behaviour (TPB), widely used to forecast behavioural intention, has also demonstrated a good predictive capacity in addictions. The aim of this study is to design and validate a Cannabis Use Intention Questionnaire (CUIQ) based on TPB. 1,011 teenagers answered a set of tests to assess attitude towards use, subjective norms, self-efficacy towards non-use, and intention to use cannabis. CUIQ had good psychometric properties. Structural Equation Modelling results confirm the predictive model on intention to use cannabis in the Spanish adolescent sample, classified as users and non-users, explaining 40% of variance of intention to consume. CUIQ is aimed at providing a better understanding of the psychological processes that lead to cannabis use and allowing the evaluation of programmes. This can be particularly useful for improving the design and implementation of selective prevention programmes.

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Informationen zur Finanzierung

This research has been carried out under the CAPPYC (Cannabis Abuse Prevention Program for Young Consumers) project, coordinated by the Fundación de Ayuda contra la Drogadicción (FAD) and co-funded by the Eu-

Geldgeber

Bibliographische Referenzen

  • Adamson, S. J. y Sellman, J. D. (2003). A prototype screening instrument for cannabis use disorder: The Cannabis Use Disorders Identification Test (CUDIT) in an alcohol-dependent clinical sample. Drug and Alcohol Review, 22, 309-315. doi:10.1080/0959523031000154454.
  • Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50, 179-211. doi:10.1016/0749-5978(91)90020-T.
  • Ajzen, I. (2002). Constructing a TPB questionnaire: Conceptual and methodological considerations.
  • Armitage, C. J. y Conner, M. (2001). Efficacy of the Theory of Planned Behaviour: a meta-analytic review. The British Journal of Social Psychology, 40, 471-499. doi:10.1348/014466601164939.
  • Armitage, C. J., Conner, M., Loach, J. y Willetts, D. (1999). Different perceptions of control: Applying an extended theory of planned behavior to legal and illegal drug use. Basic and Applied Social Psychology, 21, 301-316.
  • Bashford, J., Flett, R. y Copeland, J. (2010). The Cannabis Use Problems Identification Test (CUPIT): Development, reliability, concurrent and predictive validity among adolescents and adults. Addiction, 105, 615-625. doi:10.1111/j.1360-0443.2009.02859.x.
  • Bentler, P. M. (2004). EQS 6: Structural equation program manual. Encino, CA: Multivariate Software.
  • Boys, A., Marsden, J. y Strang, J. (2001). Understanding reasons for drug use amongst young people: a functional perspective. Health Education Research, 16, 457-469. doi:10.1093/her/16.4.457.
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2a ed.). New York, NY: Guilford Press.
  • Browne, M. V. y Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods and Research, 21, 230-258.
  • Byrne, B. M. (1988). The Self-Description Questionnaire III: Testing for equivalent factorial validity across ability. Educational and Psychological Measurement, 48, 397-406. doi:10.1177/0013164488482012.
  • Chadwick, B., Miller, M.L. y Hurd, Y.L. (2013). Cannabis use during adolescent development: susceptibility to psychiatric illness. Clearing the smokescreen: The current evidence on cannabis use. Frontiers in Psychiatry, 4, 1-8.
  • Crean, R.D., Crane, N.A. y Mason, B.J. (2011). An evidence-based review of acute and long-term effects of cannabis use on executive cognitive functions. Journal of Addiction Medicine, 5, 1-8.
  • Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Methods Plainly Speaking, 43, 121-149.
  • Elosua Oliden, P. y Zumbo, B. D. (2008). Coeficientes de fiabilidad para escalas de respuesta categórica ordenada. Psicothema, 20, 896-901.
  • EMCDDA. (2016). Informe europeo sobre drogas 2016: Tendencias y novedades. Observatorio Europeo de las Drogas y las Toxicomanías. Oficina de Publicaciones de la Unión Europea, Luxemburgo.
  • Fernández-Artamendi, S., Fernández-Hermida, J. R., García-Cueto, E., Secades-Villa, R., García-Fernández, G. y Barrial-Barbén, S. (2012). Adaptación y validación española del Adolescent-Cannabis Problems Questionnaire (CPQ-A). Adicciones, 24, 41-49.
  • Fernández-Artamendi, S., Fernández-Hermida, J. R., Muñiz-Fernández, J., Secades-Villa, R. y García-Fernández, G. (2012). Screening of cannabis-related problems among youth: The CPQ-A-S and CAST questionnaires. Substance Abuse Treatment, Prevention, and Policy, 7, 1-9. doi:10.1186/1747-597X-7-13.
  • Fonseca-Pedrero, E., Ortuño-Sierra, J., Paino, M. y Muñiz, J. (2016). Psychotic-like Experiences and Substance Use in College Students. Adicciones, 28, 144-153. doi:10.20882/adicciones.781.
  • Fornell, C. y Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
  • García-Sánchez, S., Matalí, J.L., Martín-Fernández, M., Pardo, M., Lleras, M., Castellano-Tejedor, C. y Haro, JM. (2016). Internalizing and externalizing personality and subjective effects in a sample of adolescent cannabis users. Adicciones, 28, 231-241. doi: 10.20882/adicciones.887.
  • Gonzálvez, M.T., Espada, J.P., Guillon-Riquelme, A., Secades, R. y Orgilés, M. (2016). Association between personality traits and substance use in Spanish adolescents. Adicciones, 28, 108-115. doi:10.20882/adicciones.777.
  • Hall, W. y Degenhardt, L. (2009). Adverse Health Effects of Non-medical Cannabis Use. Lancet, 374, 1383-1391.
  • Hibell, B., Guttormsson, U., Ahlström, S., Balakireva, O., Bjarnason, T., Kokkevi, A. y Kraus, L. (2012). The 2011 ESPAD Report.
  • Jöreskog, K. y Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Erlbaum.
  • Klempova, D., Sánchez, A., Vicente, J., Barrio, G., Domingo, A., Suelves, J. M., … Ramirez, V. (2009). Consumo problemático de cannabis en estudiantes españoles de 14-18 años: Validación de escalas. Estudio colaborativo entre la Delegación del Gobierno para el Plan Nacional sobre Drogas y el Observatorio Europeo de las Drogas y las Toxicomanías. Ministerio de Sanidad y Política Social.
  • Lee, C. M., Neighbors, C., Hendershot, C. S. y Grossbard, J. R. (2009). Development and preliminary validation of a Comprehensive Marijuana Motives Questionnaire. Journal of Studies on Alcohol and Drugs, 70, 279-287.
  • Legleye, S., Guignard, R., Richard, J. B., Kraus, L., Pabst, A. y Beck, F. (2015). Properties of the Cannabis Abuse Screening Test (CAST). International Journal of Methods in Psychiatric Research, 24, 170-183.
  • Legleye, S., Karila, L., Beck, F. y Reynaud, M. (2007). Validation of the CAST, a general population Cannabis Abuse Screening Test. Journal of Substance Use, 12, 233-242.
  • MacCallum, R. C, Browne, M. W. y Sugawara, H. M. (1996). Power Analysis and Determination of Sample Size for Covariance Structure Modelling. Psychological Methods, 1, 130-149.
  • Martin, G., Copeland, J., Gilmour, S., Gates, P. y Swift, W. (2006). The Adolescent Cannabis Problems Questionnaire (CPQ-A): Psychometric properties. Addictive Behaviors, 31, 2238-2248. doi:10.1016/j.addbeh.2006.03.001.
  • McMillan, B. y Conner, M. (2002). Drug use and cognitions about drug use amongst students: Changes over the university career. Journal of Youth and Adolescence, 31, 221-229.
  • McMillan, B. y Conner, M. (2003). Applying an extended version of the Theory of Planned Behavior to illicit drug use among students. Journal of Applied Social Psychology, 33, 1662-1683. doi:10.1111/j.1559-1816.2003.tb01968.x.
  • Menghrajani, P., Klaue, K., Dubois-Arber, F. y Michaud, P. A. (2005). Swiss adolescents’ and adults’ perceptions of cannabis use: a qualitative study. Health Education Research, 20, 476-484.
  • Morales-Manrique, C. C., Bueno-Cañigral, F. J., Aleixandre-Benavent, R. y Valderrama-Zurián, J. C. (2011). Creencias y motivos asociados al consumo de cannabis en población escolarizada de la ciudad de Valencia, España. Trastornos Adictivos, 13, 151-159.
  • Mulaik, S.A., James, L. R., Alstine, J. V., Bennett, N., Lind, S. y Stilwell, C. D. (1989). Evaluation of goodness of fit indices for structural equation models. Psychological Bulletin, 105, 430-445.
  • Nunnally, J. C. y Bernstein, I. J. (1995). Teoría psicométrica (3ª ed.). Madrid: McGraw-Hill.
  • Observatorio Español de las Drogas y Toxicomanías. (2014). Encuesta Estatal sobre Uso de Drogas en Estudiantes de Enseñanzas Secundarias (ESTUDES) 2012-2013. Delegación del Gobierno para el Plan Nacional sobre Drogas. Ministerio de Sanidad, Política social e Igualdad.
  • Olivar Arroyo, Á. y Carrero Berzal, V. (2007). Análisis de la intención conductual de consumir cannabis en adolescentes: desarrollo de un instrumento de medida basado en la teoría de la conducta planificada. Trastornos Adictivos, 9, 184-205. doi:10.1016/S1575-0973(07)75645-3.
  • Plancherel, B., Bolognini, M., Stephan, P., Laget, J., Chinet, L., Bernard, M. y Halfon, O. (2005). Adolescent’s beliefs about marijuana use: A comparison of regular users, past users and never/ocasional users. Journal Drug Education, 35, 131-146.
  • Podsakoff, P. M., MacKenzie, S. B. y Lee, J. Y. (2003). Common Method Biases in Behavioural Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology, 88, 879-903.
  • Rodríguez Marín, J. (1998). La funcionalidad de la Teoría de la Acción Planeada en la prevención de las conductas adictivas. En J. A. García -Rodríguez y C. López Sánchez (Eds.), Nuevas aportaciones a la prevención de las drogodependencias. Madrid, España: Síntesis.
  • Rodríguez-Kuri, S. E., Diaz-Negrete, D. B., Gracia-Gutiérrez de Velasco, S. E., Guerrero-Huesca, J. A. y Gómez-Maqueo, E. L. (2007). Capacidad predictiva de la Teoría de la Conducta Planificada en la intención y uso de drogas ilícitas entre estudiantes mexicanos. Salud Mental, 30, 68-81.
  • Rubino, T., Zamberletti, E. y Parolaro, D. (2012). Adolescent Exposure to Cannabis as a Risk Factor for Psychiatric Disorders. Journal of Psychopharmacology, 26, 177-188.
  • Saiz Galdós, J. (2009). Estudio empírico de las variables de la Teoría de la Conducta Planificada como factores de riesgo para el consumo de cocaína en tres grupos diferentes. Adicciones, 21, 187-194.
  • Satorra, A. y Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. En A. von Eye y C. C. Clogg (Eds.), Latent variables analysis: Applications to developmental research (pp. 399-419). Thousand Oaks, CA: SAGE.
  • Schafer, J. y Brown, S. A. (1991). Marijuana and cocaine effect expectancies and drug use patterns. Journal of Consulting and Clinical Psychology, 59, 558-565.
  • Topa, G. y Moriano, J. A. (2010). Theory of planned behavior and smoking: Meta-analysis and SEM model. Substance Abuse and Rehabilitation, 1, 23-33.
  • Tucker, L. R. y Lewis, C. (1973). Determination of parameters of a functional relation by factor analysis. Psychometrika, 38, 1-10.
  • UNODC. (2016). World Drug Report 2016. Oficina de las Naciones Unidas contra la Droga y el Delito (United Nations publication, Sales No. E.16.XI.7). Recuperado a partir de http://www.unodc.org/wdr2016/
  • Zumbo, B. D., Gadermann, A. M. y Zeisser, C. (2007). Ordinal Versions of Coefficients Alpha and Thera for Likert Rating Scales. Journal of Modern Applied Statistical Methods, 6, 21-29.
Fuente de los datos: Dialnet