The search was conducted in the ERIC, Psicodoc, PsycINFO, and Scopus databases, following the “PRISMA” methodology to ensure greater scientific rigor (Page et al., 2021). This search was performed in mid-April 2023, using Boolean operators in both Spanish (“conductas de riesgo” OR adicción OR ciberadicción) AND (adolescencia) and English (“risk behaviors” OR addiction OR cyber addiction) AND (adolescence). The initial results were filtered to include only scientific journal articles and were limited by date, covering the period from 2018 to April 2023, representing five full years and the month of April 2023. The PsycINFO database provided more precise filtering options in terms of subject, classification, and age group (see Table 1).

The results obtained were filtered manually by reading the titles and abstracts, followed by selection based on a series of inclusion and exclusion criteria. The inclusion criteria were: (a) the sample age should be between 12 and 17 years, inclusive, and (b) the study should describe adolescent addictive behaviors, providing relevant data.

The exclusion criteria were: (a) articles analyzing other problem behaviors not related to substance use and digital addictions, (b) documents where addictive behaviors are mentioned but the results do not provide significant contributions to understanding these behaviors, and (c) documents with samples younger than 12 years or older than 17 years.

Below is the flow diagram that summarizes the stages of the search and study selection process. This scheme, based on the PRISMA guidelines (Page et al., 2021), clearly illustrates the number of records identified, screened, excluded, and ultimately included in the review (Figure 1).

After obtaining 2,064 documents from various databases, the distribution was as follows: ERIC with search in Spanish (0), ERIC with search in English (139), Psicodoc with search in Spanish (225), Psicodoc with search in English (107), PsycINFO with search in Spanish (13), PsycINFO with search in English (1,120), Scopus with search in Spanish (2), and Scopus with search in English (458).

Duplicate articles, totaling 128, were subtracted from these results: Psicodoc with search in Spanish (1), Psicodoc with search in English (70), PsycINFO with search in Spanish (6), PsycINFO with search in English (12), Scopus with search in Spanish (1), and Scopus with search in English (38).

After eliminating duplicate articles, a total of 1,936 documents were obtained. Titles and abstracts were then reviewed, and exclusion criteria were applied: (a) the document addresses a different subject matter than the one addressed here, (b) the age range of the participants in the studies is outside the range established for this systematic review, and (c) the document relates addiction to another subject but does not provide the necessary results regarding the subject matter of this systematic review. The following articles were eliminated: ERIC with search in English (a = 126, b = 6, c = 1), Psicodoc with search in Spanish (a = 103, b = 64, c = 15), Psicodoc with search in English (a = 23, b = 4, c = 8), PsycInfo with search in Spanish (a = 6, b = 1, c = 0), PsycInfo with search in English (a = 762, b = 159 and c = 152), Scopus with search in Spanish (a = 0, b = 1, c = 0), and finally, Scopus with search in English (a = 261, b = 61, c = 81). Additionally, 52 articles were excluded for not adhering to the scientific format: ERIC with search in English (5), Psicodoc with search in Spanish (20), Psicodoc with search in English (1), PsycInfo with search in English (19), and lastly, Scopus with search in English (7).

A total of 51 documents were obtained, which were manually filtered after reading the entire document to eliminate those that did not meet the inclusion and exclusion criteria. Consequently, 10 documents were excluded because, although their abstracts presented a mean age that matched the criteria established in this systematic review, the methodology section, specifically the participant section, revealed that the age range did not meet this criterion. These exclusions were from the following databases: ERIC with search in English (1), Psicodoc with search in Spanish (2), PsycInfo with search in English (6), and Scopus with search in English (6).

A total of 41 documents were obtained from the following databases: ERIC with search in English (1), Psicodoc with search in Spanish (20), Psicodoc with search in English (1), PsycInfo with search in English (10), and Scopus with search in English (9).

The methodological quality of the included studies was assessed using the “QualSyst” scale (Kmet et al., 2004), which provides a standardized framework for appraising both quantitative and qualitative research based on criteria related to study design, sampling, analysis, and reporting (14 items for quantitative studies and 10 for qualitative studies). Each item is rated on a scale from 0 to 2, with the denominator adjusted when a criterion is not applicable, yielding a final score expressed as a percentage. According to this metric, values above 75% are classified as high quality, those between 55–75% as moderate quality, and those below 55% as low quality. In the present study, scores ranged from 79.19 to 100%, which overall reflects a high methodological quality (see Table 2).

A total of 41 studies conducted across 15 countries were included in this review. The largest proportion of studies originated from Spain (n = 15), followed by the United States (n = 7) and Brazil (n = 3). Other countries represented were South Korea (n = 2), Italy (n = 2), Turkey (n = 2), Australia (n = 2), and single studies from Argentina, Switzerland, Colombia, China, Tunisia, Germany, Slovenia, and Mexico.

Regarding the types of addictions, categories were not mutually exclusive, as several studies examined multiple behaviors or substance uses. The most frequently investigated was alcohol use (n = 18), followed by tobacco use (n = 11), cannabis use (n = 10), problematic internet use (n = 8), gambling (n = 7), video gaming (n = 6), and problematic smartphone use (n = 5).

Regarding the size of the study samples, there is notable variety, ranging from general studies with 27,900 participants to more personal studies with just 2 participants. Specifically, 4.88% of the articles have a sample size of over 15,000 users, 2.44% have between 10,000 and 14,000 users, 4.88% have between 10,000 and 15,000 users, 26.83% have between 5,000 and 10,000 users, 17.07% have between 500 and 1,000 users, 36.58% have between 100 and 500 users, and 7.32% have fewer than 100 users.

The age range for the established sample was 12 to 17 years, as selected for the systematic review. However, about a third of the selected studies have fully addressed this stage of adolescence. The most frequently cited age in the articles was 15 years, while the least cited was 12 years. This is an important aspect to consider, since addictions often begin at early ages.

The review of evidence provides a comprehensive and multidimensional perspective on the factors associated with the use of substances (alcohol, tobacco, cannabis, cocaine) and problematic technology use (mobile phones, internet, video games, social media), as well as the phenomenon of polyconsumption among adolescents. These behaviors, rooted in a complex interaction of motivational, familial, social, and psychological variables, are characterized by their heterogeneity and high comorbidity.

Regarding alcohol consumption, the primary motivations include the pursuit of fun, social disinhibition, avoidance of emotional distress, and peer pressure. These motivations exhibit gender differences, with adolescent girls often justifying their consumption for social acceptance, while boys associate it with reinforcing ideals of masculinity (Dos Santos et al., 2018). Family environment is also a critical factor; according to (Rodrigues et al., 2018), 40% of adolescents reported a family history of excessive alcohol use, with first exposure commonly occurring at home. Additionally, peer pressure from high-risk groups and a lack of parental control exacerbate consumption (González-Ramos et al., 2018). Older adolescents with greater purchasing power are at significantly higher risk (Díaz et al., 2018). The consequences include tolerance to negative effects such as hangovers or shame, while academic and social implications receive less acknowledgment (Wicki et al., 2018). Early initiation (before age 14) is associated with a higher risk of problematic consumption and antisocial behaviors (Villanueva et al., 2019; Rial et al., 2020). Protective factors include positive family relationships, community involvement, and strategies focusing on self-efficacy and peer support (Clements-Nolle et al., 2019; Hernández et al., 2022).

Tobacco consumption is similarly influenced by economic and social factors, such as financial accessibility and sensation-seeking, particularly among men (Díaz et al., 2018; Martínez-Fernández et al., 2018). Early initiation increases the risk of antisocial behavior and cognitive deterioration (Villanueva et al., 2019). Additionally, electronic cigarettes, often mistakenly perceived as less harmful, promote dual use with traditional cigarettes, significantly heightening dependence (Strong et al., 2019; Tackett et al., 2021).

Similarly, cannabis use often begins at an early age, with an average initiation age of 12.9 years, and is associated with risks such as dependency (67.1% in regular users) and progression to stronger substances like opioids and methamphetamines (Jones and McCance-Katz, 2019; Matalí et al., 2018). Impulsivity and frequent alcohol consumption further elevate this risk (González-Roz et al., 2021). Furthermore, cannabis consumption is linked to the development of psychopathologies (Díaz et al., 2018).

Problematic mobile phone use negatively impacts psychological health, reducing self-esteem, sleep quality, and social relationships. It is associated with aggressive behaviors, low self-control, and increased risk-taking, with only 25% of adolescents managing to self-regulate their usage (Pastor et al., 2022). Girls primarily use mobile phones for social purposes, while boys prioritize leisure (Lee et al., 2018). This pattern extends to social media use, where poor self-regulation leads 21% of adolescents to addictive behaviors, linked to anxiety, cyberbullying, and substance use (Cimadevilla et al., 2019; Machado et al., 2018). Furthermore, Internet Gaming Disorder, affecting 2.8% of adolescents, is associated with social exclusion, low self-esteem, and executive dysfunction (Warburton et al., 2022). The potential for video game addiction is driven by unmet psychological needs, such as achievement or socialization, and may exacerbate psychotic disorders in vulnerable adolescents (Bekir and Çelik, 2019; Ricci et al., 2023).

Adolescent boys over 16 show a higher prevalence of gambling behaviors (Caselles et al., 2018; Hing et al., 2022). Impulsivity and sensation-seeking often motivate this activity, frequently linked to alcohol and substance use, particularly in online gambling. Cocaine use, while less prevalent, is associated with other risk behaviors like online gambling, with adolescent gamblers twice as likely to use cocaine compared to the general population (Isorna et al., 2022).

The phenomenon of polyconsumption in adolescents highlights the interaction of social, familial, and psychological factors. Motivations include intrinsic ones (e.g., fun, disinhibition) and extrinsic ones (e.g., peer pressure), with gender differences: girls often justify these behaviors for social acceptance, whereas boys link them to displays of status (Dos Santos et al., 2018). Family and social environments are key determinants, with economic availability playing a critical role (Díaz et al., 2018). Polyconsumers exhibit deficits in executive functions and dysfunctional coping styles (Villanueva et al., 2019). Early initiation increases the likelihood of transitioning to stronger substances, such as opioids and cocaine (Jones and McCance-Katz, 2019). Moreover, technological dependency exacerbates alcohol and tobacco consumption (Cimadevilla et al., 2019).

When analyzing the selected documents, the most studied addictions over the past 5 years were identified as alcohol, tobacco, cannabis, cocaine, video games, gambling, internet, social networks, and smartphones. To achieve the main objective of this systematic review, a qualitative analysis was conducted using the technological tool ATLAS.ti Web (version 3.15.0; ATLAS.ti Scientific Software Development GmbH, 2022). This process provided more rigorous information on the subtopics addressed within each addiction (see Figure 2).

Overall, the results indicate that an early onset of substance use increases the risk of addiction in subsequent years (Hernández et al., 2022; Villanueva et al., 2019). The risk of developing an addiction also increases with age and is more prevalent among males and individuals with greater economic resources (Díaz et al., 2018). The motivations for consumption are influenced by interpersonal and sociocultural factors (Dos Santos et al., 2018).

Adolescence is a critical life period characterized by ongoing biological, behavioral, and social transformations that drive human development (Bustamante et al., 2022; Zammit et al., 2018). Changes in brain structure and function, along with influences from the social environment, can increase the likelihood of adolescents engaging in problematic behaviors (Viejo and Ortega-Ruiz, 2015). This makes adolescence a stage particularly prone to risky and reckless behaviors (Steinberg, 2008).

Tobacco and alcohol use represent the most common types of substance abuse among European adolescents (Dudok and Piko, 2023). Motivations for consumption are influenced by personal, social, and cultural factors (Dos Santos et al., 2018; Hernández et al., 2022). The availability and consumption of addictive substances pose a serious social problem, leading to significant health disorders for young people and affecting their environment (Pérez-Fuentes et al., 2018). The initial age of alcohol consumption is around 13.4 years (Rial et al., 2020).

Following this first experience, prevalence increases notably, with consumption often escalating from sporadic to habitual and excessive (Martínez-Fernández et al., 2018; González-Ramos et al., 2018; Rodrigues et al., 2018). Addiction to alcohol results in various negative consequences for minors, primarily impacting their physical, mental, and emotional health, and can even lead to school failure (Calero et al., 2019; Clements-Nolle et al., 2019; González-Ramos et al., 2018; Wartberg et al., 2021; Wicki et al., 2018) and violent situations. Another significant problem associated with alcohol is its normalization in society (Villanueva et al., 2019), the ease of acquisition, and the various places of consumption, which include not only social gatherings but also one’s own home (Rodrigues et al., 2018).

Tobacco dependence among adolescents has been observed to have an earlier onset compared to other substances (Barragán et al., 2016; Villanueva et al., 2019), and shows considerable prevalence (Martínez-Fernández et al., 2018).

An increase in prevalence with age has been observed: according to the results of the HBSC Study (Ministerio de Sanidad, 2018), the percentage of individuals who report daily tobacco use increases with age, peaking among 17-18-year-olds. At this age, minimal differences in consumption are observed between males and females.

Various forms of tobacco use have been identified, including cigarettes, cigars, water pipes, vapes, and e-cigarettes, with the latter being the most prominent according to recent research. The motivation for consumption appears to be driven by sensation seeking (Camelo et al., 2019; Martínez-Fernández et al., 2018; Silveira et al., 2019; Strong et al., 2019; Tackett et al., 2021). Negative impacts include increased impulsivity (González-Roz et al., 2021) and a higher propensity for other risky behaviors (Demissie et al., 2017). The peer relationships and peer pressure significantly influence the acquisition of this addiction (Villanueva et al., 2019), along with academic failure. Family structure also plays a crucial role, particularly in reconstructed families (Camelo et al., 2019; Isorna et al., 2022), where age and gender are significant factors, with older males being more likely to consume (Díaz et al., 2018; Peruga et al., 2022). Finally, economic availability directly influences consumption, as adolescents with greater financial resources tend to consume more (Díaz et al., 2018).

The average age of onset for cannabis use is around 13 years, with the mean age for daily use being approximately 13.8 years (Matalí et al., 2018). Over time, there has been an observed increase in the prevalence of cannabis use (Martínez-Fernández et al., 2018). The motivation for consuming this substance appears to be linked to sensation seeking (Camelo et al., 2019; Martínez-Fernández et al., 2018; Silveira et al., 2019), as well as a desire to escape from situations that generate negative feelings or to achieve a state of relaxation (Matalí et al., 2018). Among the negative consequences of cannabis consumption, low self-esteem (Camelo et al., 2019), increased impulsivity (González-Roz et al., 2021), and the manifestation of violent and problematic behaviors (Villanueva et al., 2019) stand out.

According to the ESPAD report, cannabis is the most consumed illicit substance among European students (Ministerio de Sanidad, 2020). They are considered at risk of severe dependence, a trend potentially driven by the emergence of new variants of cannabis and the increasing potency of its derivatives in recent years (Ministerio de Sanidad, 2020).

Cannabis use by adolescents is influenced by several factors, including family background, belonging to reconstructed families, economic resources, and peer groups. Peer pressure exerts a dual influence: surrounding oneself with friends who consume increases the likelihood of addiction (Hahlbeck and Vito, 2022), while adolescents lacking adequate social skills experience fear and pressure due to the potential rejection by their peers (Matalí et al., 2018; Villanueva et al., 2019).

The results of the HBSC Study emphasize that cannabis use is more prevalent among males than females, particularly within the 17-18-year-old demographic (Ministerio de Sanidad, 2018).

Additionally, age, duration of use, and economic status also negatively impact cannabis use among minors (Díaz et al., 2018). Cannabis use is often associated with the poly-consumption of substances harmful to health (Jones and McCance-Katz, 2019).

Due to the growing concern about addiction to both traditional and new behavioral substances, several studies have analyzed this issue. For instance, Salamó et al. (2010) investigate alcohol consumption patterns, social influence, and risk perception, while Rial et al. (2020) examine the impact of early onset of consumption and identify related variables, such as substance use within the family environment or among peers. Additionally, the consumption of not only traditional cigarettes but also electronic or vapor cigarettes has become prevalent (Demissie et al., 2017).

Other studies have explored polydrug use among adolescents. For example, Barragán et al. (2016) examine the factors associated with alcohol, tobacco, and cannabis use in high school students. Similarly, Peruga et al. (2022) analyze the use of electronic cigarettes and alcohol in high school students, while Calero-Plaza et al. (2020) investigate adolescent poly-consumption of alcohol, cannabis, and marijuana, linking it to violent and delinquent behaviors. In addition, Isorna et al. (2022) analyze addiction to the Internet, gambling, tobacco, alcohol, cocaine, and cannabis.

On the other hand, behavioral addictions are defined as impulsive and repetitive behaviors characterized by a loss of control, a strong compulsive desire to engage in them, persistent emotional discomfort, and continuation of the behavior despite its serious consequences (De Sola et al., 2013).

Adolescents use Information and Communication Technologies (ICTs) more frequently and for longer periods of time, often without adequate parental supervision, in various settings such as education, home, or leisure time. They use these tools for a range of purposes, from maintaining social relationships to performing academic tasks or entertaining themselves, either alone or with friends, which can lead to problematic use, especially between the ages of 12 and 17 (Gairín and Mercader, 2018). Consequently, some studies analyze problematic internet use based on risk profiles, family environment characteristics, and behavioral and psychological factors (Arrivillaga et al., 2021). The average age of onset of daily internet use is between 6 and 15 years old (Kaya and Dalgiç, 2021), and the prevalence of internet addiction among adolescents is notable, reaching 21% (Machado et al., 2018). Negative consequences of internet use include low self-esteem (Peris et al., 2018) and lack of self-regulation (Pastor et al., 2022). Significant data related to internet addiction have been observed, such as a higher risk among males at the age of 17, despite an increasing prevalence among females, and low emotional regulation (Arrivillaga et al., 2021). Additionally, the importance of parental control in reducing addictive behaviors is highlighted (Isorna et al., 2022).

Gambling, which involves the use of money or bets, typically begins between the ages of 12 and 13 (Caselles et al., 2018; Isorna et al., 2022). Studies, such as Hing et al. (2022), highlight the ease of access to these games for adolescents. A high prevalence of this activity is observed among adolescents, exacerbated by the normalization of gambling within their immediate environment (Caselles et al., 2018). The primary motivations for gambling include stress management, socialization, and the pursuit of positive emotions (Grande-Gosende et al., 2019). Studies indicate that various types of gambling are readily available and easily accessible (Martínez-Loredo et al., 2019). This addiction is also influenced by the minor’s age, gender, and the social acceptance of gambling within both the family environment and peer groups (Caselles et al., 2018).

Playing video games is not inherently negative, but it can sometimes develop into a pathological practice (Hidalgo-Fuentes, 2023a; Pereira, 2021). The estimated global prevalence of gaming addiction is 3.5% (Ricci et al., 2023), and studies such as Buja et al. (2020) estimate that nearly a third of gamers experience difficulties related to playing video games. The motivations behind this problem include fun, the search for new sensations, the ease of playing from home with peers, the constant positive reinforcement from prizes and winning, and the adventure experience it provides, fulfilling the psychological needs of adolescents (Bekir and Çelik, 2019). Video games help them manage stress and develop positive emotions (Grande-Gosende et al., 2019), serving as a method of coping with social difficulties (López-Fernández et al., 2020). Male adolescents, particularly younger ones, are most associated with this problematic practice (Macur and Pontes, 2021; Warburton et al., 2022). Factors such as executive dysfunction, lack of self-regulation, impulsivity, and unmet needs outside the virtual world contribute to this issue. Adolescents from disconnected and disaffected family environments are also at increased risk (López-Fernández et al., 2020; Warburton et al., 2022). Other studies highlight profiles with low agreeableness and responsibility in males, and low extraversion and responsibility in females (López-Fernández et al., 2021). The repercussions of excessive video game playing include decreased self-control (Macur and Pontes, 2021), altered sleep patterns, and an increased risk of engaging in harmful behaviors such as substance use, alcohol, tobacco, or gambling on slot machines (Cimadevilla et al., 2019). Additionally, a correlation has been observed between excessive video game playing and mental health symptoms, as well as increased severity in behavioral problems (Richard et al., 2023).

Adolescents at high risk of smartphone addiction exhibited significantly more severe levels of psychopathologies across all dimensions of the Youth Self-Report scale (Lee et al., 2018). This addiction affects psychological factors such as anxiety, behavioral inhibition system, and aggression (Lee et al., 2020), leading to a greater tendency toward risky behaviors and lower self-control, particularly in girls (Dou et al., 2020).

Lastly, social networks have a significant influence on daily life and are widely used by adolescents. Some individuals are more susceptible to developing addictions to these platforms, particularly those with an introverted profile (Muñoz and Ramírez, 2016). It has been observed that females are more likely to experience symptoms of addiction, excessive use, and nomophobia compared to males, with these tendencies being more pronounced in the age range of 12 to 14 years (Peris et al., 2018). This phenomenon can adversely impact the mental health of adolescents, as it encourages constant comparison with others, decreases self-esteem, increases exposure to online bullying, and promotes dependence and social isolation, all of which affect emotional well-being (Herrera-Peco et al., 2023).

This study synthesizes findings from a range of sources to provide a comprehensive and multidimensional perspective on adolescent substance use initiation and abuse. By analyzing substance use alongside behavioral patterns, it identifies emerging trends and offers actionable insights to inform the development of evidence-based prevention and intervention strategies. The findings emphasize the need for tailored prevention approaches that address early onset, gender-specific risk factors, and the influence of family environment and peer relationships.

For clinicians, the study underscores the importance of incorporating routine screenings for substance use and behavioral addictions into adolescent health assessments. For educators and policymakers, it provides critical insights to design targeted educational campaigns and enforce policies that limit access to harmful substances. This integrative approach fills significant gaps in current research, offering valuable guidance to stakeholders aiming to reduce the risks associated with adolescent substance use and behavioral addictions.