697Universitas Psychologica1657-92672011-2777Pontificia Universidad JaverianaColombiauniversitas.psych@javeriana.edu.co6972764008ArtículosPredictive Models of Relapses and Recovery in Young People with Risky Alcohol Consumption*Modelos predictivos de recaídas y de recuperación en jóvenes con consumo
riesgoso de alcoholhttps://orcid.org/0000-0002-5239-6700Vargas-NavarroPedroapvargas04@ucatólica.edu.cohttps://orcid.org/0000-0003-3273-3658Londoño-PérezConstanzahttps://orcid.org/0000-0002-8136-5380Avendaño-PrietoBertha LucíaUniversidad El BosqueUniversidad El BosqueColombiaUniversidad Cooperativa de ColombiaUniversidad Cooperativa de ColombiaColombiaUniversidad Católica
de ColombiaUniversidad Católica
de ColombiaColombiaa Correspondence author. Email: pvargas04@ucatolica.edu.coJanuary-December2024231602202222032023https://creativecommons.org/licenses/by/4.0/Esta obra está bajo una Licencia Creative Commons Atribución 4.0 Internacional.Abstract
Risky alcohol consumption is the precursor of dependence. As relapses and recovery influence the success and cost of treatments, the objective of this work is to construct two predictive models—one for relapses and one for recovery—for individuals who engage in risky alcohol consumption. For this purpose, a cross-sectional study was conducted on 646 individuals of medium socioeconomic status, and the following instruments were applied: the AUDIT, Zung scales, a questionnaire of beliefs about alcohol consumption, two questionnaires that predict relapse and recovery, and the family APGAR. From the initial sample, 250 people (with a 64% female demographic, aged between 18 and 35) were identified as having risky alcohol consumption. A structural equations model concluded that the most influential variables for relapse were favorable beliefs about alcohol consumption, early onset, consumer friends, and academic, family, and social issues; whereas those that favored recovery were: good family functioning and late age of onset. It is recommended to expand the sample to be more heterogeneous to generalize the proposed models and compare individuals with and without risky alcohol consumption.
Resumen
El consumo riesgoso de alcohol marca el comienzo hacia la dependencia. Dado que las recaídas y la recuperación afectan el éxito y costo de los tratamientos, el presente trabajo tiene como objetivo generar la construcción de dos modelos predictivos, uno para las recaídas y otro para la recuperación, en personas con consumo riesgoso de alcohol. El estudio fue predictivo transversal y se aplicaron los siguientes instrumentos a 646 personas de nivel socioeconómico medio: el Audit, las escalas de Zung, un cuestionario de creencias sobre consumo de alcohol, dos cuestionarios predictores de recaídas y recuperación, y el Apgar familiar. De la muestra inicial, se determinó que 250 personas (64% de sexo femenino con edades entre 18 y 35 años) tenían consumo riesgoso. A través de un modelo de ecuaciones estructurales se determinó que las variables más significativas para recaer son las creencias favorables en torno al consumo de alcohol, el inicio temprano, los amigos consumidores y los problemas académicos, familiares y sociales; mientras que las que favorecen la recuperación son el buen funcionamiento familiar y la edad tardía de inicio. Se recomienda trabajar con una muestra más heterogénea que permita generalizar los modelos propuestos e incluir una comparación entre personas con y sin consumo riesgoso.
Keywordsconsumptionalcoholrelapserecoverystructural equationsPalabras claveconsumoalcoholrecaídarecuperaciónecuaciones estructuralesHow to citeVargas-Navarro, P.,
Londoño-Pérez, C., & Avendaño-Prieto, B. (2024). Predictive
Models of Relapses and Recovery in Young People with Risky Alcohol Consumption. Universitas Psychologica, 23, 1-XX. https://doi.org/10.11144/Javeriana.upsy23.pmrr
Mind-body and Mother Earth are inseparable (Tizón, 2015), it is the essence of the human, but it is forgotten, and in addictions and other health problems it is essential to consider this integration to understand that substance use disorders are multifactorial and include personal, family, sociocultural and environmental indicators.
Interest in health prevention has increased over the past decade given the difficulties in treating established disorders, which increase in crisis situations such as the Covid-19 pandemic (Tizón, 2020). Alcohol risk consumption is considered to exist when the individual has been inebriated more than once in the last year or has drunk more than four units of liquor (in women) or five (in men) within two hours (McCambridge et al., 2011; National Institute on Drug Abuse [NIDA], 2020; Obradors-Rial et al., 2014). Risk is estimated because it increases the eventuality of causing adverse effects for the consumer or others (Babor et al., 2001; World Health Organization [WHO] & Gobierno de España Ministerio de Sanidad y Consumo [GEMSC], 1994).
Among the personal factors found in the literature as a predictor of abusive alcohol consumption is the early onset, associated with the establishment of standard of risky consumption behavior. Bourque et al. (2016) and Pilatti et al. (2013), show that the pattern of alcohol consumption established at an early onset will likely last or increase over time. Kjeldsen et al. (2019) argue that early prevention of alcohol consumption in adolescence has a positive impact on consumption behavior.
Similarly, among the variables that predict the increase in alcohol consumption are positive expectations about their effects, consumption with friends, little acceptance of the consequences, believing that it favors social interaction and emotional control (Negrete et al., 2015; Pilatti et al., 2013; Londoño et al., 2005; Obradors-Rial et al., 2014). Among these factors is also the low ability to withstand group pressure, extroversion, under personal control, lack of responsibility, background, and school behavioral problems (Arias Zapata et al., 2012; Cabrejas, 2013; Pilatti et al., 2013; Quiñonez et al., 2016; Weichold et al., 2014).
Regarding family and social factors involved in the emergence and maintenance of risky alcohol consumption, it is evident that young people imitate abusive behaviors of their relatives and peers and turn out in ingesting alcohol in excess (Castaño-Pérez & Calderón-Vallejo, 2014; Lee et al., 2004; Negrete et al., 2015; Obradors-Rial et al., 2014), situation that worsens when there are economic problems (Obradors-Rial et al., 2014). In opposition, the establishment of rules by parents concerning their alcohol consumption and low alcohol consumption (although not mothers) differentiates adolescents with zero or low consumption from those who consume (Aguirre-Guiza et al., 2017; Pilatti et al., 2013; Weichold et al., 2014).
In addition, the absence of family unity and the use of substances promotes overuse (Pilatti et al., 2013; Soto et al., 2016; Vargas et al., 2015; Weichold et al., 2014); however, it has been found that the assessment of the family interaction that the adolescent has is not related to his alcohol consumption (Trujillo-Guerrero et al., 2016) particularly in women (Ohannessian et al., 2016).
A global understanding of the issue of risky alcohol consumption implies an ecosystem vision (Bronfenbrenner, 1987; Newcomb, 1995) in which individual consumption is immersed (Ministerio de Salud y Protección Social [MSPS], 2013). For example, advertising and music that present positive ads about drinking can induce the early onset of alcohol consumption (Castaño-Pérez & Calderón-Vallejo, 2014) and ignore the negative impacts of the drink (Valentine et al., 2010). In addition, an educational environment with abundant disputes where psychoactive substances are affordable, assist excessive alcohol consumption (Soto et al., 2016).
It is necessary to consider the process of change that includes relapse and recovery (Prochaska et al., 2008). In relapse, people return to consumption which is usual to occur (Simonelli, 2005; National Institute on Drug Abuse [NIDA], 2017), and should not be considered as a failure because it allows to learn from the problem (Fleury et al., 2016).
Causes of relapse include withdrawal syndrome (physical signs and psychological symptoms of discomfort), which occurs when alcohol consumption stops or decreases (Becker, 2008) Some syndromes such as the severity of alcohol consumption, anxiety about alcohol consumption in intake (individuals with severe craving), the age of onset of consumption, the presence of long-term social and personal problems related to alcohol (breaking relationships with family and friends, hopelessness), finances (unemployment, lack of income and poverty) or with legal problems (Kuria, 2013). Likewise, relapses are more common in individuals who lack coping and self-efficacy skills (US Department of Health and Human Services, 2000) and in general, with intrapersonal variables such as emotional regulation in decision-making considered in the somatic marker hypothesis (Blanco-Álvarez & Jiménez-Morales, 2015; Michelini et al., 2016).
Other factors associated with relapses are risky or dependent consumption, mainly when it has been maintained for more than six years (Tuithof et al., 2014) Individual tends to present aggressive behaviors more than impulsivity, negative emotional states(depression and anxiety), social pressure for substance use, interpersonal conflicts, low tolerance to frustration in interpersonal relationships, negative physical states, positive interpersonal emotional states and the urgency and temptation of alcohol use (Baars et al., 2013; Martin et al., 2011). The presence of only one of these factors increases the possibility of relapse (Tuithof et al., 2014).
Beliefs regarding consumption have shown its preeminence to prevent alcohol consumption in young people (Londoño, 2007; Aravena & Londoño, 2019). The need to address the problem of relapses is recognized in order to generate procedures to prevent, control and face them (Witkiewitz & Marlatt, 2005).
Among the components that enable recovery are the different types of aids (aimed exclusively at the individual or including the family, in external or residential consultation, integral or with a single approach), aspects of the person (spirituality, commitment, comprehension of the effects of alcohol, understanding and realization of the transformation process, registration of relapses, coping with craving and errors), the family (support to solve difficulties and manage stress and performance), and social (near and far social networks) (Allen et al., 2014; Dermatis & Galanter, 2016; Schwarzer, 2014; Korcha et al., 2016; Lyytikäinen, 2016; Sandoz, 2014; Tripodi et al., 2010).
In Colombia, 2.7% out of survey young respondents are rated as a drinker at risk. The highest proportion of risk drinkers is located in the 18 to 44 age range, predominantly male (De la Espriella et al., 2015). In the Americas, excessive alcohol consumption is estimated to be a high-risk practice, more than half of high school students who reported alcohol consumption in the past month did so excessively. High-risk behaviors, such as early onset and excessive alcohol consumption, warn of the priority of developing selective and indicated prevention programs (Comisión Interamericana para el Control del Abuso de Drogas [CICAD] & Organización de los Estados Americanos [OEA], 2019).
These programs are based on predictive models or analyses that are generally used to forecast behavioral trends and patterns or relationships between variables and the development of these prediction models can be done through different statistical techniques (Agüero & Minvielle, 2017), among which are the models of structural equations.
Preliminary evidence justifies the importance of designing a predictive relapse and recovery model for young people with risky alcohol consumption to channel early prevention actions. The models established on the subject have focused on the analysis of dependency leaving aside the study of risky consumption. In order to deepen understanding of this field and facilitate its prediction and intervention, it was proposed as general objective that a predictive model of relapses and recovery in young people was designed, based on the integration of personal, family, sociocultural and environmental factors found in the literature. This model contributes to understanding the problem of addictions and to drawing up a plan to reduce the uncertainty generated by this situation by including an ecological perspective.
<bold>Methods</bold><bold>Type of study</bold>
According to Ato et al. (2013) the study is of a cross-cutting predictive type since it sought to explore the functional relationships among the different personal, social, and situational factors linked to the intake of risky alcohol consumption.
<bold>Variables </bold>
Socio-demographic variables (Starting Age of consumption, Age, Sex, Socioeconomic and Educational level, Civil Status, Profession or Job, Psychiatric Background and other Illnesses, Medicine consumption and living arrangements). Personal, family, social, cultural and environmental factors, beliefs around alcohol consumption, friends who consume, depression and anxiety.
<bold>Participants</bold>
646 university students were surveyed, of which 250 drinkers who were interested in recovering from substance abuse were selected. 98% out of participants were single and this same percentage did not work; only 6% out of respondents reported consumption of other substances. The sample was selected for convenience. The average age of the participants was 20-year-old, with an age range between 18 and 31 years old, the average age of onset of consumption was 15.7 years, the female sex represented 64%. 44% were at the average socioeconomic level, 78.3% had no psychiatric history, 82.6% reported no diseases, 80,6% did not take medicines and 78.7% lived with their family.
<bold>Instruments</bold>
Sociodemographic Data Record Sheet: It includes personal data such as age, sex, socioeconomic and educational level, marital status, profession or trade, psychiatric and other illness history, drug use and people with who they live.
Test AUDIT: WHO's Identification Test for Alcohol Consumption Disorders estimates the pattern of risky or harmful alcohol consumption, consisting of 10 items that measure the level of risk (Babor et al., 2001).
Questionnaire of relapse predictors in young alcohol consumers (Vargas et al., 2023), has 29 items whose objective is to evaluate personal, family, social, cultural, and environmental factors that trigger recidivisms in alcohol consumption in young people from 18 to 35 years old. This questionnaire has various response options, the internal consistency index of this instrument obtained with Cronbach’s alpha with all items was 0.71 and the alpha values in the different dimensions were 0.73, 0.92, 0.83, 0.77, 0.71. 0.52 and 0.69.
Questionnaire of recovery promoters in young alcohol consumers (Vargas et al., 2023), this instrument is composed of 32 items, its objective is to evaluate personal, family, social, cultural, and environmental factors that facilitate the maintenance of regulation or the complete abandonment of alcohol consumption in young people from 18 to 35 years old and has various response options. The value of Cronbach's alpha coefficient, used to establish internal consistency, with all items was 0.98 and each factor was 0.98, 0.92, 0.94, and 0.95 respectively.
Zung Self-Rating Depression Scale (1965) quantifies the presence of symptoms of depression, was validated in Colombia by Lezama (2012), consists of 20 items measuring dominant affection and compromised psychological and physiological components. It has four answer options. The internal consistency evaluated with Cronbach’s alpha was 0.55.
Zung Self-Rating Anxiety Scale (1971), validated in Colombian population by Cabarcas & Córdoba Mena (2012), seeks to determine the presence of symptoms of anxiety, it consists of 20 items that measure dominant affection and the psychological and physiological components compromised. It has four response options that go from never to always, has an adequate level of internal consistency, the Cronbach’s alpha was 0.73.
Belief Questionnaire on alcohol consumption designed by Valencia et al. (2009) composed of 20 items, it was based on the Belief Model which includes the following dimensions: perception of risk/vulnerability/severity, perceived barriers, perceived benefits, subjective rules and keys to action, the options answer were in Likert Scale, the internal consistency determined with the Cronbach´s alpha score of 0.87.
WHO short-version family APGAR (1978), adapted for Colombia by Forero et al. (2006), assesses the level of family dysfunction through five questions with answer choices ranging from never to always, this scale has an internal consistency level of 0.79.
<bold>Procedure </bold>
The research was carried out in four phases: Phase 1. A bibliographical review was carried out on risky alcohol consumption. Phase 2. A letter was sent that included the objectives, the request to participate in the study and the informed consent to the directives of two institutions. It had the endorsement of the Ethics Committee of the Catholic University of Colombia through Act number 4 of October 7, 2018. Phase 3. The instruments were applied in person, individually and in a group with the informed consent of the participants and anonymity and confidentiality were guaranteed. Phase 4. The database was prepared and the analysis was carried out.
<bold>Data analysis</bold>
To decide what type of statistics should be used, the distribution of variables was initially considered with the Kolmogorov-Smirnov test. To determine the best fit model, bivariate analyses were performed among all predictor variables and the two criterion variables (Relapse and Recovery). The model's goodness-of-fit study followed Pilatti’s et al. (2013) instructions, the reason for Chi-squared was obtained on CMIN/DF degrees of freedom, the CFI and GFI indices, the RMSEA index, the non-standard adjustment index, or Tucker-Lewis (TLI), and the Incremental Fit Index (IFI) (Leal-Costa et al., 2016). The model proposed involves the relationship between the variables of risky alcohol consumption in young people, relapses and recovery. An analysis of adjustment of the empirical model to the theorist with Structural equations were performed with the software SPSS version 25 and the AMOS of SPSS version 21.
<bold>Results</bold>
To determine the best fit model, bivariate analyses were performed among all predictor variables and the two criterion variables (Relapse and Recovery). The relapse variable had a normal distribution, but the recovery variable was not distributed normally K-S=0.04 y p=0.20 for relapse and K-S=0.12 y p=0.00 for recovery. In the gender difference analysis, t for Student was used for unrelated relapse samples and the non-parametric Mann-Whitney's U test for recovery. No statistically significant differences were found by sex or relapse or recovery; t of Student= 1.62 and p= 0.12 for relapse and Z=- 1.12 and p=0.27 for recovery, therefore, it was not considered appropriate to differentiate models by this variable.
Concerning the relapse variable, no statistically significant differences were found between psychiatric background variables. Do you have any illnesses? Do you take any medications? and who do you live with? for this analysis the one-way Anova was used.
Concerning the relapse variable, no statistically significant differences were found between: psychiatric background variables (F=1.67, p=0.19), do you have any illnesses? (F=2.11, p=0.15), do you take any medications? (F=1.39, p=0.24) and who do you live with? (F=0.20, p=0.89) for this analysis the one-way Anova was used.
Anxiety and depression, assessed through the Zung instrument, did not contribute to the study. The family APGAR used to determine family function turned out to be one of the relevant variables.
<bold>Relapses</bold>
The factors that contributed to the predictive model of relapse in risky alcohol consumption were early onset of consumption, alcohol-consuming friends, academic, family, social problems and beliefs around alcohol consumption (Table 1 and Figure 1).
<italic>Significant correlations with Relapses</italic>
Table 1 Significant correlations with Relapses
*p < 0.01.
CCA: beliefs on alcohol consumption
The model is shown in Figure 1. The magnitude and sign of the estimated parameters find the correlation with relapses as follows: the early onset of consumption at -0.15. (< 0.01), alcohol-consumer friends -0.11. (< 0.01), academic problems 0.05 (< 0.01), relatives 0.14 (< 0.01) and social 0.08 (< 0.0.) and beliefs on alcohol consumption 0.34 (< 0.01).
Predictive
relapse Model.
Figure 1. Predictive
relapse Model.
<bold>Recovery </bold>
The Mann Whitney's U test was used to analyze the association between the recovery variable and the risk variable, (Z = 2.705, p >0.005). In order to establish whether there are statistically significant differences in recovery in psychiatric history. Do you have any illnesses? Do you take any medications? Who do you live with? Kruskal-Wallis' the one-way non-parametric Anova was used. No statistically significant differences were found with these variables. Table 2 and Figure 2 include variables that have statistically significant differences in recovery.
<italic>Significant correlations with Recovery</italic>
Table 2 Significant correlations with Recovery
*p<.05. **p<.01
Predictive model of recovery.
Figure 2. Predictive model of recovery.
Factors that are part of the predictive model of recovery in risky alcohol consumption were age of onset, level of consumption and family functioning.
In Figure 2 the results find the relationship with recovery as follows: Age of onset at 0.08 (p=0.04), Audit consumption level -0.50 (< 0.01.) and risk -0.09 and family functioning 0.13 (< 0.01). The covariance or joint variation between Onset and Risk is 0.19, Onset and Audit 0.31, and Audit and Risk 0.40.
Table 3 shows the goodness-of-fit results of the Relapse and Recovery models, the GFI≥0.90, RMSEA ≤0.05, IFI, TLI, CFI ≥0.90 indexes, have a good fit of the tested models (Hu & Bentler, 1999).
<italic>Goodness-of-fit
statistics for Relapse and Recovery models</italic>
Table 3 Goodness-of-fit
statistics for Relapse and Recovery models
CMIN/DF: Reason for chi squared
on degrees of freedom; GFI: Overall goodness-of-fit index; IFI: Incremental
adjustment rate; TLI - Trucker-Lewis Index; CFI - Comparative Adjustment Index;
RMSEA - Mean Quadratic Error.
<bold>Discussion and conclusions</bold>
The general objective of this work was to develop a predictive model for relapse and recovery, in people with risky alcohol consumption. The models found integrate personal, family, sociocultural and environmental factors reported by various authors (Bourque et al., 2016; Bronfenbrenner, 1987; Caamano-Isorna et al., 2020; Castaño-Pérez & Calderón-Vallejo, 2014; Fagan et al., 2015; Lee et al., 2004; Moure-Rodriguez et al., 2018; Pilatti et al., 2013; Scoppetta & Ortiz Garzón, 2021). The findings contribute to the understanding of the problem of addictions and in particular the risky consumption of alcohol, important for early prevention.
Two predictive models were formed, relapse and recovery that integrate personal, family, sociocultural and environmental factors reported by various authors, verified with the application to a sample of the population, the findings contribute to the understanding of the problem of addictions, and particularly to the risky consumption of alcohol, important for the priority early prevention in actions in this field.
The early onset of alcohol consumption that is part of the factors of the predictive relapse model has been associated with the establishment of a risky standard consumption behavior (Bourque et al., 2016; Pilatti et al., 2013). As in other studies, it was found that use with friends is among the variables that predict the increase in alcohol consumption (Negrete et al., 2015; Pilatti et al., 2013; Londoño et al., 2005; Obradors-Rial et al., 2014).
On the other hand, the proposed models include academic, family and social issues, described as behavioral problems in school by other authors (Arias Zapata et al., 2012; Cabrejas, 2013; Pilatti et al., 2013; Weichold et al., 2014) or family and school models who drink in excess (Castaño-Pérez & Calderón-Vallejo, 2014; Lee et al., 2004; Negrete et al., 2015; Obradors-Rial et al., 2014). Lack of harmony (Pilatti et al., 2013; Soto et al., 2016; 2015, Weichold et al., 2014). Likewise, beliefs on alcohol consumption have been related to the use of alcohol by young people in other investigations (Londoño, 2007; Aravena & Londoño, 2019). The application of family APGAR was relevant for measuring family functioning since this variable was significant in both models. Advertising and music that present positive ads about drinking can induce the early onset of alcohol consumption reported by Castaño-Pérez & Calderón-Vallejo (2014) and ignore the negative impacts of alcohol mentioned by Valentine et al. (2010) were not relevant in this study. Probably in the Colombian context there is not enough advertising against alcohol and young people only see the positive aspect of consumption that favors sociability.
Many consumers who abuse alcohol are not aware of the situation, do not present a desire for control and therefore, they feel not to need to recover. In addition, a large proportion of the drinkers stated in various items of the Questionnaires on relapse and recovery predictors, the option does not apply. Denial and stigma influenced many participants not to answer the Questionnaire on relapse predictors and recovery in young people with risky alcohol consumption. since at the time of application some denied consumption even when the AUDIT showed otherwise.
Among the components that enable recovery are the different types of aids (aimed exclusively at the individual or including the family, in external or residential consultation, integral or with a single approach), aspects of the person (spirituality, commitment, comprehension of the effects of alcohol, understanding and realization of the transformation process, registration of relapses, coping with craving and errors), the family (support to solve difficulties and manage stress and performance), and social (near and far networks) (Allen et al., 2014; Dermatis & Galanter, 2016; Schwarzer, 2014; Korcha et al., 2016; Lyytikäinen, 2016; Sandoz, 2014; Tripodi et al., 2010) Neither, the early onset or level of consumption are mentioned. AUDIT results of -0.05 and risk of -0.09 indicate that variables that measured the level of consumption (risky consumption) although they are important to recovery have less weight than age of onset and family functioning variables.
In relation to recovery, the findings of this study make it possible to conclude that the later the onset of use and the lower the level of consumption, the greater the recovery. The age of onset contributes more to recovery than to relapse and lower consumption of parents and better family functioning the easier recovery is. This aspect contributes to the prevention and prognosis linked to the importance of parent behavior with alcohol consumption and family harmony for recovery, results that confirm what is indicated by Allen et al. (2014), Dermatis & Galanter (2016), Schwarzer (2014), Korcha et al. (2016), Lyytikäinen (2016), Sandoz (2014) and Tripodi et al. (2010).
The limitations of this study related to the sample as it mostly corresponded to average socioeconomic levels, two-thirds of them made up of women. In future studies the sample should be more heterogeneous.
This model contributes to the understanding of addiction issues and in particular to alcohol risky consumption, which is important for priority early prevention in actions in this field.
The aspect related to the absence of consumption of parents and a good family functioning contributes to the prevention and prognosis of risky consumption.
<bold>References</bold>Agüero, S., & Minvielle, M. (2017). Técnicas de aprendizaje para predecir atributos no funcionales en componentes de aplicaciones Android [Tesis de pregrado]. Universidad Nacional del Centro de la Provincia de Buenos Aires. https://bit.ly/31YSrzBAgüeroS.MinvielleM.Técnicas de aprendizaje para predecir atributos no funcionales en componentes de aplicaciones Android2017https://bit.ly/31YSrzBTesis de pregradoAguirre-Guiza, N. C., Aldana-Pinzón, O. B., & Bonilla-Ibáñez, C. P. (2017). Factores familiares de riesgo de consumo de sustancias psicoactivas en estudiantes de una institución de educación media técnica de Colombia. Revista de Salud Pública, 19, 3-9. https://doi.org/10.15446/rsap.v19n1.41785Aguirre-GuizaN. C.Aldana-PinzónO. B.Bonilla-IbáñezC. P.Factores familiares de riesgo de consumo de
sustancias psicoactivas en estudiantes de una institución de educación media
técnica de ColombiaRevista de Salud Pública2017https://doi.org/10.15446/rsap.v19n1.41785Allen, J., Mohatt, G.V., Fok, C.C.T., Henry, D., & Burkett, R. (2014). A protective factors model for alcohol abuse and suicide prevention among Alaska Native youth. American Journal of Community Psychology, 54(1-2), 125-139. https://doi:10.1007/s10464-014-9661-3AllenJ.MohattG.V.FokC.C.T.HenryD.BurkettR.A protective factors model for alcohol abuse and
suicide prevention among Alaska Native youthAmerican Journal of Community Psychology2014https://doi:10.1007/s10464-014-9661-3Aravena, S.F.C., & Londoño C. (2019). Creencias sobre el consumo de alcohol en jóvenes colombianos y chilenos. Acta Colombiana de Psicología, 22(2), 178-184. http://www.doi.org/10.14718/ACP.2019.22.2.9AravenaS.F.C.Creencias sobre el
consumo de alcohol en jóvenes colombianos y chilenosActa Colombiana de Psicología2019http://www.doi.org/10.14718/ACP.2019.22.2.9Arias Zapata, F. J., Calderón Vallejo, G. A., Cano Bedoya, V. H., & Castaño Pérez, G. A. (2012). Consumo de alcohol y factores de riesgo en estudiantes de dos universidades colombianas. El Ágora USB, 12(1), 127–141. https://doi.org/10.21500/16578031.228Arias ZapataF. J.Calderón VallejoG. A.Cano BedoyaV. H.Castaño PérezG. A.Consumo de alcohol y factores de riesgo en estudiantes de dos universidades
colombianasEl Ágora USB2012https://doi.org/10.21500/16578031.228Ato, M., López, J., & Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. Anales de Psicología, 29(3), 1038-1059. https://doi:10.6018/analesps.29.3.178511AtoM.LópezJ.BenaventeA.Un sistema de clasificación de los diseños de
investigación en psicologíaAnales de Psicología2013https://doi:10.6018/analesps.29.3.178511Baars, M.Y., Matthias, J., Müller, M. J., Bernd Gallhofer, B., & Netter, P. (2013). Relapse (number of detoxifications) in abstinent male alcohol-dependent patients as related to personality traits and types of tolerance to frustration. Neuropsychobiology, 67, 241–248. https://doi:10.1159/000350483BaarsM.Y.MatthiasJ.MüllerM. J.Bernd GallhoferB.NetterP.Relapse (number of detoxifications) in abstinent male
alcohol-dependent patients as related to personality traits and types of
tolerance to frustrationNeuropsychobiology2013https://doi:10.1159/000350483Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. (2001). Cuestionario de Identificación de los Trastornos debidos al Consumo de Alcohol (AUDIT). Pautas para su utilización en Atención Primaria. OMS/Departamento de Salud Mental y Dependencia de Sustancias. http://www.descentralizadrogas.gov.co/wp-content/uploads/2015/05/AUDITmanualSpanish.pdfBaborT. F.Higgins-BiddleJ. C.SaundersJ. B.MonteiroM.Cuestionario de Identificación de los Trastornos debidos al Consumo de Alcohol (AUDIT) Pautas para su utilización en Atención Primaria2001http://www.descentralizadrogas.gov.co/wp-content/uploads/2015/05/AUDITmanualSpanish.pdfBecker, H. C. (2008). Alcohol dependence, Withdrawal, and relapse. Alcohol Health & Research World, 31(4), 348. https://pubs.niaaa.nih.gov/publications/arh314/348- 361.pdfBeckerH. C.Alcohol dependence, Withdrawal, and relapseAlcohol Health & Research World2008https://pubs.niaaa.nih.gov/publications/arh314/348Blanco-Álvarez, T., & Jiménez-Morales, S. (2015). Factores de riesgo que influyen en la recaída de consumo de drogas lícitas e ilícitas en adolescentes atendidos en el Instituto sobre Alcoholismo y Farmacodependencia/Risk Factors Affecting Relapse of Licit and Illirosoncit Drug Use in Adolescents Assisted by the Institute of Alcoholism and Drug Dependence (IAFA). Revista Costarricense de Psicología, 34(2). 147-157. http://dx.doi.org/10.22544/rcps.v34i02.0Blanco-ÁlvarezT.Jiménez-MoralesS.Factores de riesgo
que influyen en la recaída de consumo de drogas lícitas e ilícitas en
adolescentes atendidos en el Instituto sobre Alcoholismo y Farmacodependencia/Risk Factors Affecting
Relapse of Licit and Illirosoncit Drug Use in Adolescents Assisted by the Institute of Alcoholism and Drug Dependence (IAFA)Revista Costarricense de Psicología2015http://dx.doi.org/10.22544/rcps.v34i02.0Bourque, J., Baker. T. E., Dagher. A., Evans. A. C., Garavan. H., Leyton. M., Séguin, J. R., Pihl, R, & Conrod. P. J. (2016). Effects of delaying binge drinking on adolescent brain development: a longitudinal neuroimaging study. BMC Psychiatry, 16(1), 445. https://doi.org/10.1186/s12888-016-1148-3BourqueJ.Baker. T. E.Dagher. A.Effects of delaying
binge drinking on adolescent brain development: a longitudinal neuroimaging
studyBMC Psychiatry2016https://doi.org/10.1186/s12888-016-1148-3Bronfenbrenner, U. (1987). La ecología del desarrollo humano. Ediciones Paidós.BronfenbrennerU.La ecología del desarrollo humano1987Caamano-Isorna, F., Adkins, A., Aliev, F., Moure-Rodríguez, L., & Dick, D. M. (2020). Population Attributable Fraction of Early Age of Onset of Alcohol Use in Alcohol Abuse and Dependence: A 3-Year Follow-Up Study in University Students. International Journal of Environmental Research and Public Health, 17(6), 2159. https://doi.org/10.3390/ijerph17062159Caamano-IsornaF.AdkinsA.AlievF.Moure-RodríguezL.DickD. M.Population
Attributable Fraction of Early Age of Onset of Alcohol Use in Alcohol Abuse and
Dependence: A 3-Year Follow-Up Study in University StudentsInternational Journal of Environmental Research and Public Health2020https://doi.org/10.3390/ijerph17062159Cabarcas Merlano, A. J., & Córdoba Mena, K. G. (2012). Descripción de los valores de ansiedad y consistencia interna de la escala Zung ansiedad en una muestra de la población del Salado corregimiento del Carmen de Bolívar. Universidad Tecnológica Bolívar. https://hdl.handle.net/20.500.12585/1949Cabarcas MerlanoA. J.Córdoba MenaK. G.Descripción
de los valores de ansiedad y consistencia interna de la escala Zung ansiedad en
una muestra de la población del Salado corregimiento del Carmen de BolívarUniversidad Tecnológica Bolívar2012https://hdl.handle.net/20.500.12585/1949Cabrejas, B. (2013). Control personal y creencias en el consumo de alcohol en jóvenes universitarios [Doctoral dissertation. Tesis de grado]. Universidad de Salamanca. Escuela de Medicina, Salamanca. https://gredos.usal.es/bitstream/handle/10366/123080/DPPMMLHM_CabrejasMartinez_Beatriz_Resumen_de_Tesis.pdf;jsessionid=6E40547EDE13C12CDA8A541530EB69EA?sequence=1CabrejasB.Control personal y creencias en el consumo de alcohol en jóvenes universitarios2013https://gredos.usal.es/bitstream/handle/10366/123080/DPPMMLHM_CabrejasMartinez_Beatriz_Resumen_de_Tesis.pdf;jsessionid=6E40547EDE13C12CDA8A541530EB69EA?sequence=1Doctoral
dissertation. Tesis de gradoCastaño-Pérez, G. A., & Calderón-Vallejo, G. A. (2014). Problems associated with alcohol consumption by university students. Revista Latino-Americana de Enfermagem, 22(5), 739-746. http://dx.doi.org/10.1590/0104-1169.3579.2475Castaño-PérezG. A.Calderón-VallejoG. A.Problems
associated with alcohol consumption by university studentsRevista Latino-Americana de Enfermagem2014http://dx.doi.org/10.1590/0104-1169.3579.2475Comisión Interamericana para el Control del Abuso de Drogas (CICAD), & Organización de los Estados Americanos (OEA). (2019). Informe sobre el consumo de drogas en Las Américas. https://www.seguridad.gob.sv/cna/wp-content/uploads/2019/03/Informe-sobre-el-consumo-de-drogas-en-las-Américas-2019.pdf. Accessed June 15, 2021.Comisión Interamericana para el Control del Abuso de Drogas (CICAD)Organización de los Estados
Americanos (OEA)Informe sobre el consumo de drogas en Las Américas2019https://www.seguridad.gob.sv/cna/wp-content/uploads/2019/03/Informe-sobre-el-consumo-de-drogas-en-las-Américas-2019.pdfDermatis, H., & Galanter, M. (2016). The Role of Twelve-Step-Related Spirituality in Addiction Recovery. Journal of Religion and Health, 55(2). 510-521. https://doi.org/10.1007/s10943-015-0019-4DermatisH.GalanterM.The Role of Twelve-Step-Related
Spirituality in Addiction RecoveryJournal of Religion and Health2016https://doi.org/10.1007/s10943-015-0019-4De la Espriella, R. A., Rodríguez, V., Rincón, C. J., Cabrera, D., Pérez, S. J., & Gómez-Restrepo, C. (2015). Consumo de alcohol en la población colombiana. Encuesta Nacional de Salud Mental 2015. Revista Colombiana de Psiquiatría, 45(S1). 76-88. https://doi:10.1016/j.rcp.2016.05.002De la EspriellaR. A.RodríguezV.RincónC. J.CabreraD.PérezS. J.Gómez-RestrepoC.Consumo de alcohol en la población colombiana. Encuesta Nacional de
Salud Mental 2015Revista Colombiana de Psiquiatría2015Fagan, A. A., Wright, E. M., & Pinchevsky, G. M. (2015). A multi-level analysis of the impact of neighborhood structural and social factors on adolescent substance use. Drug and Alcohol Dependence, 153, 180-186. https://doi.org/10.1016/j.drugalcdep.2015.05.022FaganA. A.WrightE. M.PinchevskyG. M.A multi-level analysis of the impact of neighborhood structural and
social factors on adolescent substance useDrug and Alcohol Dependence2015Fleury, M. J., Djouini. A., Huynh. C., Tremblay. J., Ferland. F., Ménard. J. M., & Belleville. G. (2016). Remission from Substance Use Disorders: A Systematic Review and Meta-Analysis. Drug and Alcohol Dependence, 168, 293-306. https://doi.org/10.1016/j.drugalcdep.2016.08.625FleuryM. J.Djouini. A.Huynh. C.Remission from Substance Use Disorders: A Systematic Review and Meta-AnalysisDrug and Alcohol Dependence2016https://doi.org/10.1016/j.drugalcdep.2016.08.625Forero, L. M., Avendaño, M. C., Cubillos, Z. J., & Campo-Arias, A. (2006). Consistencia interna y análisis de factores de la escala APGAR para evaluar el funcionamiento familiar en estudiantes de básica secundaria. Revista colombiana de psiquiatría, 35(1), 23-29. https://www.redalyc.org/pdf/806/80635103.pdfForeroL. M.AvendañoM. C.CubillosZ. J.Campo-AriasA.Consistencia interna y análisis de factores de la
escala APGAR para evaluar el funcionamiento familiar en estudiantes de básica
secundariaRevista colombiana de psiquiatría2006https://www.redalyc.org/pdf/806/80635103.pdfHu, L., & Bentler, P. M. (1999). Cut-off Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118HuL.BentlerP. M.Cut-off Criteria for Fit Indexes in Covariance Structure Analysis:
Conventional Criteria versus New AlternativesStructural Equation Modelling: A Multidisciplinary Journal1999https://doi.org/10.1080/10705519909540118Korcha, R. A., Polcin. D., & Bond. J. (2016). Interaction of Motivation and Social Support on Abstinence Among Recovery Home Residents. Journal of Drug Issues, 46(3). 164-177. https://doi.org/10.1177/0022042616629514KorchaR. A.Polcin. DInteraction of
Motivation and Social Support on Abstinence Among Recovery Home ResidentsJournal of Drug Issues2016https://doi.org/10.1177/0022042616629514Kjeldsen, A., Enstad, F., Evans-Whipp, T., Toumbourou, J. W., & Von Soest, T. (2019). Predicting Hazardous Drinking in Late Adolescence/Young Adulthood from Early and Excessive Adolescent Drinking: A Longitudinal Cross-National Study of Norwegian and Australian Adolescents. BMC Public Health, 19(1), 790. https://doi.org/10.1186/s12889-019-7099-0KjeldsenA.EnstadF.Evans-WhippT.ToumbourouJ. W.Von SoestT.Predicting Hazardous Drinking in Late
Adolescence/Young Adulthood from Early and Excessive Adolescent Drinking: A
Longitudinal Cross-National Study of Norwegian and Australian AdolescentsBMC Public Health2019https://doi.org/10.1186/s12889-019-7099-0Kuria, M. W. (2013). Factors associated with relapse and remission of alcohol dependent persons after community-based treatment. Open Journal of Psychiatry, 3(2). https://doi:10.4236/ojpsych.2013.32025KuriaM. W.Factors associated with relapse and remission of alcohol dependent persons
after community-based treatmentOpen Journal of Psychiatry2013https://doi:10.4236/ojpsych.2013.32025Leal-Costa, C., Tirado-González, S., Rodríguez-Marín, J., & Vander-Hofstadt-Román, C. J. (2016). Psychometric Properties Of the Health Professionals Communication Skills Scale (HP-CSS). International Journal of Clinical and Health Psychology, 16(1), 76-86. https://doi.org/10.1016/j.ijchp.2015.04.001Leal-CostaC.Tirado-GonzálezS.Rodríguez-MarínJ.Vander-Hofstadt-RománC. J.Psychometric Properties Of the Health
Professionals Communication Skills Scale (HP-CSS)International Journal of Clinical and Health Psychology2016https://doi.org/10.1016/j.ijchp.2015.04.001Lee, G., Akers, R. L., & Borg, M. J. (2004). Social Learning and Structural Factors in Adolescent Substance Use. Criminology Review, 5(1). 17-34. http://www.westerncriminology.org/documents/WCR/v05n1/article_pdfs/lee.pdfLeeG.AkersR. L.BorgM. J.Social Learning and Structural Factors in Adolescent
Substance UseCriminology Review2004http://www.westerncriminology.org/documents/WCR/v05n1/article_pdfs/lee.pdfLezama, S. (2012). Propiedades psicométricas de la escala Zung para síntomas depresivos en población adolescente escolarizada colombiana. Psychologia. Avances de la Disciplina, 6(1), 91-101. https://www.redalyc.org/articulo.oa?id=297225770010LezamaS.Propiedades psicométricas de la escala Zung para síntomas depresivos en
población adolescente escolarizada colombianaPsychologia Avances de la Disciplina2012https://www.redalyc.org/articulo.oa?id=297225770010Londoño, C. (2007). Modelo cognitivo-social integrado para la prevención del abuso en el consumo de alcohol. Tipica, Boletín Electrónico de Salud Escolar, 3(2).LondoñoC.Modelo cognitivo-social integrado para la
prevención del abuso en el consumo de alcoholTipica, Boletín Electrónico de Salud Escolar2007Londoño, C., García Hernández, W., Valencia Lara, S. C., & Vinaccia Alpi, S. (2005). Expectativas frente al consumo de alcohol en jóvenes universitarios colombianos. Anales de Psicología, 21(2), 259-267.LondoñoC.García HernándezW.Valencia LaraS. C.Vinaccia AlpiS.Expectativas frente al consumo de alcohol
en jóvenes universitarios colombianosAnales de Psicología2005Lyytikäinen, L. (2016). Mutual Support and Recovery in the Russian Alcoholics Anonymous Online Community. Nordic Studies on Alcohol and Drugs, 33(2), 151-172. https://doi.org/10.1515/nsad-2016-0013LyytikäinenL.Mutual Support
and Recovery in the Russian Alcoholics Anonymous Online CommunityNordic Studies on Alcohol and Drugs2016https://doi.org/10.1515/nsad-2016-0013Martin, R. A., MacKinnon, S. M., Johnson, J. E., Myers, M. G., Cook, T. A. R., & Rohsenow, D. J. (2011). The Alcohol Relapse Situation Appraisal Questionnaire: Development and Validation. Drug and Alcohol Dependence, 116, 45–51. https://doi.org/10.1016/j.drugalcdep.2010.11.022MartinR. A.MacKinnonS. M.JohnsonJ. E.MyersM. G.CookT. A. R.RohsenowD. J.The Alcohol Relapse Situation Appraisal Questionnaire: Development
and ValidationDrug and Alcohol Dependence2011McCambridge, J., McAlaney, J., & Rowe, R. (2011). Adult Consequences of Late Adolescent Alcohol Consumption: A Systematic Review of Cohort Studies. PLoS Med, 8(2), e1000413. https://doi.org/10.1371/journal.pmed.1000413McCambridgeJ.McAlaneyJ.RoweR.Adult Consequences of Late Adolescent Alcohol Consumption: A Systematic
Review of Cohort StudiesPLoS Med2011https://doi.org/10.1371/journal.pmed.1000413Michelini, Y., Acuña, I., & Godoy, J. C. (2016). Emociones, toma de decisiones y consumo de alcohol en jóvenes universitarios. Suma Psicológica, 23(1), 42-50. https://doi.org/10.1016/j.sumpsi.2016.01.001MicheliniY.AcuñaI.GodoyJ. C.Emociones, toma de
decisiones y consumo de alcohol en jóvenes universitariosSuma Psicológica2016https://doi.org/10.1016/j.sumpsi.2016.01.001Ministerio de Salud y Protección Social (MSPS). (2013). Estrategia Nacional de respuesta integral frente al consumo de alcohol en Colombia.https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/PP/ENT/estrategia-nacional-alcohol-colombia.pdfMinisterio de Salud y Protección Social (MSPS)Estrategia Nacional de respuesta integral frente al consumo de alcohol en Colombia2013https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/PP/ENT/estrategia-nacional-alcohol-colombia.pdfMoure-Rodriguez, L., Carbia, C., Lopez-Caneda, E., Corral Varela, M., Cadaveira, F., & Caamaño-Isorna, F. (2018). Trends in alcohol use among young people according to the pattern of consumption on starting university: A 9-year follow-up study. PloS one, 13(4), e0193741. https://doi.org/10.1371/journal.pone.0193741Moure-RodriguezL.CarbiaC.Lopez-CanedaE.Corral VarelaM.CadaveiraF.Caamaño-IsornaF.Trends in alcohol
use among young people according to the pattern of consumption on starting
university: A 9-year follow-up studyPloS one2018https://doi.org/10.1371/journal.pone.0193741National Institute on Drug Abuse (NIDA). (2017). Easy-to-Read Drug Facts. Recovery and Treatment. https://easyread.drugabuse.gov/sites/default/files/EasyToRead_RecoveryTreatment_012017.pdfNational Institute on Drug Abuse (NIDA)Easy-to-Read Drug Facts Recovery and Treatment2017https://easyread.drugabuse.gov/sites/default/files/EasyToRead_RecoveryTreatment_012017.pdfNational Institute on Drug Abuse (NIDA). (2020). Binge drinking. https://www.niaaa.nih.gov/sites/default/files/publications/BingeDrinking_0.pdfNational Institute on Drug Abuse (NIDA)Binge drinking2020https://www.niaaa.nih.gov/sites/default/files/publications/BingeDrinking_0.pdfNegrete, D. B. D., Hernández, J. L. A., Kuri. S. E. R., & Cáceres, C. F. (2015). Comparación de tres modelos de riesgo de uso nocivo de alcohol en estudiantes mexicanos. Acta de Investigación Psicológica, 5(2), 2047-2061. https://www.redalyc.org/articulo.oa?id=358942803008NegreteD. B. D.HernándezJ. L. A.Kuri. S. E. R.& CáceresComparación
de tres modelos de riesgo de uso nocivo de alcohol en estudiantes mexicanosActa de Investigación Psicológica2015https://www.redalyc.org/articulo.oa?id=358942803008Newcomb, M. D. (1995). Identifying High-Risk Youth: Prevalence and Patterns of Adolescent Drug Abuse. In Adolescent drug abus.: Clinical assessment and therapeutic interventions (pp. 7-38). National Institute on Drug Abuse (NIDA).https://archives.drugabuse.gov/sites/default/files/monograph156.pdfNewcombM. D.Identifying High-Risk Youth: Prevalence and Patterns
of Adolescent Drug AbuseAdolescent drug abus: Clinical assessment and therapeutic interventions1995https://archives.drugabuse.gov/sites/default/files/monograph156.pdfObradors-Rial, N., Ariza. C., & Muntaner. C. (2014). Consumo de riesgo de alcohol y factores asociados en adolescentes de 15 a 16 años de la Cataluña Central: diferencias entre ámbito rural y urbano. Gaceta Sanitaria, 28(5), 381-385. http://dx.doi.org/10.1016/j.gaceta.2014.04.004Obradors-RialN.ArizaC.MuntanerC.Consumo de riesgo de alcohol y factores
asociados en adolescentes de 15 a 16 años de la Cataluña Central: diferencias
entre ámbito rural y urbanoGaceta Sanitaria2014http://dx.doi.org/10.1016/j.gaceta.2014.04.004Ohannessian, C. M., Flannery. K. M., Simpson. E., & Russell. B. S. (2016). Family Functioning and Adolescent Alcohol Use: A Moderated Mediation Analysis. Journal of Adolescence, 49, 19-27. https://doi.org/10.1016/j.adolescence.2016.02.009OhannessianC. M.Flannery. K. M.Simpson. E.Family Functioning and Adolescent Alcohol Use: A Moderated
Mediation AnalysisJournal of Adolescence2016https://doi.org/10.1016/j.adolescence.2016.02.009Pilatti, A., Brussino, S. A., & Godoy, J. C. (2013). Factores que influyen en el consumo de alcohol de adolescentes argentinos: un path análisis prospectivo. Revista de Psicología, 22(1), 22. https://doi.org/10.5354/0719-0581.2013.27716PilattiA.BrussinoS. A.GodoyJ. C.Factores que influyen en el consumo de alcohol de
adolescentes argentinos: un path análisis
prospectivoRevista de Psicología2013https://doi.org/10.5354/0719-0581.2013.27716Prochaska, J. O., Redding, C. A., & Evers, K. E. (2008). The Transtheoretical Model and Stages of Change. In K. Glanz, B. K. Rimer, & K. Viswanath, Health Behavior and Health Education (4 th. Edition, pp. 97-102). Jossey-Bass. https://psycnet.apa.org/record/2008-17146-005ProchaskaJ. O.ReddingC. A.EversK. E.Health Behavior and Health Education2008https://psycnet.apa.org/record/2008-17146-005Quiñonez, J. J., Peña, D. L., Salas, C., & Torres, Y. (2016). Factores personales y familiares para el abuso del alcohol en adolescentes colombianos de 13 a 17 años. Universitas Médica, 57(3), 307-322. https://doi:10.11144/Javeriana.umed57-3.fpfaQuiñonezJ. J.PeñaD. L.SalasC.TorresY.Factores personales y familiares para el abuso del alcohol en adolescentes
colombianos de 13 a 17 añosUniversitas Médica2016https://doi:10.11144/Javeriana.umed57-3.fpfaSandoz, J. (2014). Finding God Through the Spirituality of the 12 Steps of Alcoholics Anonymous. Religions, 5(4), 948-960. https://doi.org/10.3390/rel5040948SandozJ.Finding
God Through the Spirituality of the 12 Steps of Alcoholics AnonymousReligions2014https://doi.org/10.3390/rel5040948Schwarzer, R. (2014) The Health Action Process Approach (HAPA). http://userpage.fu-berlin.de/health/hapa.htmSchwarzerR.The Health Action Process Approach (HAPA)2014http://userpage.fu-berlin.de/health/hapa.htmScoppetta, O. & Ortiz Garzón, E. (2021). Modelos Ecológicos del Desarrollo aplicados al consumo de drogas ilícitas: una revisión sistemática. Psicología desde el Caribe, 38(2), 167-188. https://doi.org/10.14482/psdc.38.2.158.1ScoppettaO.Ortiz GarzónE.Modelos
Ecológicos del Desarrollo aplicados al consumo de drogas ilícitas: una revisión
sistemáticaPsicología desde el Caribe2021https://doi.org/10.14482/psdc.38.2.158.1Simonelli, M. C. (2005). Relapse: A Concept Analysis. Nursing Forum, 40(1), 3. https://doi.org/10.1111/j.1744-6198.2005.00003.xSimonelliM. C.Relapse: A Concept AnalysisNursing Forum2005https://doi.org/10.1111/j.1744-6198.2005.00003.xSoto, K. E., Carrillo, M. H., Cassiani, C. A., Munevar, Á. M. C., & Cardona, C. M. (2016). Factores relacionados con el consumo de sustancias psicoactivas en una institución educativa de Jamundí Valle, Colombia. Revista Colombiana de Psiquiatría, 45(1), 2-7. https://doi.org/10.1016/j.rcp.2015.06.001SotoK. E.CarrilloM. H.CassianiC. A.MunevarÁ. M. C.CardonaC. M.Factores relacionados con el consumo de sustancias psicoactivas en una
institución educativa de Jamundí Valle, ColombiaRevista Colombiana de Psiquiatría2016https://doi.org/10.1016/j.rcp.2015.06.001Tizón, J. (2015). Psicopatología del poder: un ensayo sobre la perversión y la corrupción. Herder Editorial.TizónJ.Psicopatología del poder: un ensayo sobre la perversión y la corrupción2015Tizón, J. (2020). Salud emocional en tiempos de crisis. Herder Editorial.TizónJ.Salud emocional en tiempos de crisis2020Tripodi, S. J., Bender, K., Litschge, C., & Vaughn, M. G. (2010). Interventions for Reducing Adolescent Alcohol Abuse: A Meta-Analytic Review. Archives of Pediatrics & Adolescent Medicine, 164(1), 85-91. https://doi:10.1001/archpediatrics.2009.235TripodiS. J.BenderK.LitschgeC.VaughnM. G.Interventions for Reducing Adolescent Alcohol Abuse: A Meta-Analytic ReviewArchives of Pediatrics & Adolescent Medicine2010https://doi:10.1001/archpediatrics.2009.235Tuithof, M., Ten Have, M., VandenBrinkb, W., Volleberghc, W., & Ron de Graaf, R. (2014). Alcohol Consumption and Symptoms as Predictors for Relapse of DSM-5 Alcohol Use Disorder. Drug and Alcohol Dependence, 140, 85-91. https://doi.org/10.1016/j.drugalcdep.2014.03.035TuithofM.Ten HaveM.VandenBrinkbW.VolleberghcW.Ron de GraafR.Alcohol Consumption and
Symptoms as Predictors for Relapse of DSM-5 Alcohol Use DisorderDrug and Alcohol Dependence2014https://doi.org/10.1016/j.drugalcdep.2014.03.035Trujillo-Guerrero, T. J., Vázquez-Cruz, E., & Córdova-Soriano, J. A. (2016). Percepción de la funcionalidad familiar y el consumo de alcohol en adolescentes. Atención Familiar, 23(3), 100-103. https://doi.org/10.1016/j.af.2016.07.003Trujillo-GuerreroT. J.Vázquez-CruzE.Córdova-SorianoJ. A.Percepción de la
funcionalidad familiar y el consumo de alcohol en adolescentesAtención Familiar2016https://doi.org/10.1016/j.af.2016.07.003US Department of Health and Human Services. (2000). 10th special report to the US Congress on alcohol and health. Bethesda. MD: National Institute on Alcohol Abuse and Alcoholism. http://www.lafe.san.gva.es/c/document_library/get_file?uuid=fcea1678-2021-4b1f-be41-31305295f8a2&groupId=18US Department of Health and Human Services10th special report to the US Congress on alcohol and health Bethesda2000http://www.lafe.san.gva.es/c/document_library/get_file?uuid=fcea1678-2021-4b1f-be41-31305295f8a2&groupId=18Valencia, C., Londoño, C., Amézquita, M., Cortés, J., Guerra, M., Castiblanco, A., & Ordóñez, J. (2009). Diseño del cuestionario de creencias referidas al consumo de alcohol para jóvenes universitarios. Diversitas. Perspectivas en Psicología, 5(2), 337-347. https://doi.org/10.15332/s1794-9998.2009.0002.09ValenciaC.LondoñoC.AmézquitaM.CortésJ.GuerraM.CastiblancoA.OrdóñezJ.Diseño del cuestionario de creencias referidas al consumo de alcohol
para jóvenes universitariosDiversitas. Perspectivas en Psicología2009https://doi.org/10.15332/s1794-9998.2009.0002.09Valentine, G., Jayne, M., Gould, M., & Keenan, J. (2010). Family life and alcohol consumption. Joseph Roundtree Foundation. http://www.ias.org.uk/uploads/pdf/Underage%20drinking%20docs/alcohol-family-life-full.pdfValentineG.JayneM.GouldM.KeenanJ.Family life and alcohol consumption2010http://www.ias.org.uk/uploads/pdf/Underage%20drinking%20docs/alcohol-family-life-full.pdfVargas, P., Londoño Pérez, C. & Avendaño-Prieto, B. L. (2023). Diseño de dos cuestionarios para evaluar recaídas y recuperación en consumo riesgoso de alcohol. Health and Addictions/ Salud y Drogas, 23(1), 41-59. https://doi.org/10.21134/haaj.v23i1.641VargasP.Londoño PérezC.Avendaño-PrietoB. L.Diseño de dos cuestionarios para evaluar recaídas y recuperación
en consumo riesgoso de alcoholHealth and Addictions/ Salud y Drogas2023https://doi.org/10.21134/haaj.v23i1.641Vargas, P., Parra Vera, M. D., Arévalo Zamora, C., Cifuentes Gaitán, L. K., Valero Carvajal, J., & de Jaramillo, M. S. (2015). Estructura y tipología familiar en pacientes con dependencia o abuso de sustancias psicoactivas en un centro de rehabilitación de adicciones en el Municipio de Chía, Cundinamarca. Revista Colombiana de Psiquiatría, 44(3). https://doi.org/10.1016/j.rcp.2015.02.007VargasP.Parra VeraM. D.Arévalo ZamoraC.Cifuentes GaitánL. K.Valero CarvajalJ.JaramilloM. S.Estructura y
tipología familiar en pacientes con dependencia o abuso de sustancias
psicoactivas en un centro de rehabilitación de adicciones en el Municipio de
Chía, CundinamarcaRevista Colombiana de Psiquiatría2015https://doi.org/10.1016/j.rcp.2015.02.007Weichold, K., Wiesner, M. F., & Silbereisen, R. K. (2014). Childhood Predictors and Mid-Adolescent Correlates of Developmental Trajectories of Alcohol Use Among Male and Female Youth. Journal of Youth and Adolescence, 43(5), 698-716. https://doi.org/10.1007/s10964-013-0014-6WeicholdK.WiesnerM. F.SilbereisenR. K.Childhood Predictors and Mid-Adolescent Correlates of Developmental
Trajectories of Alcohol Use Among Male and Female YouthJournal of Youth and Adolescence2014https://doi.org/10.1007/s10964-013-0014-6Witkiewitz, K., Marlatt, G. A., & Walker, D. (2005). Mindfulness-Based Relapse Prevention for Alcohol and Substance Use Disorders. Journal of Cognitive Psychotherapy, 19(3), 211-228. https://doi.org/10.1016/j.addbeh.2012.04.001WitkiewitzK.MarlattG. A.WalkerD.Mindfulness-Based Relapse Prevention for Alcohol and Substance
Use DisordersJournal of Cognitive Psychotherapy2005https://doi.org/10.1016/j.addbeh.2012.04.001World Health Organization (WHO), & Gobierno de España Ministerio de Sanidad y Consumo (GEMSC). (1994). Glosario de términos de alcohol y drogas. https://www.minjusticia.gov.co/programas-co/ODC/Publicaciones/Publicaciones/CO031052008-glosario%20drogas.pdfWorld Health Organization (WHO), & Gobierno de España Ministerio de Sanidad y Consumo (GEMSC)Glosario de términos de alcohol y drogas1994https://www.minjusticia.gov.co/programas-co/ODC/Publicaciones/Publicaciones/CO031052008-glosario%20drogas.pdfNotes