Risk Perception and Neuro-Emotional Development in Adolescent Athletes: Psychometric Validation of the ESTUDES Scales for Preventive Guidance Contexts

Organized sports play a crucial role in fostering both physical and psychological well-being among adolescents, equipping them with essential skills like emotional regulation, self-efficacy, and resilience. These attributes are paramount in mitigating the risks associated with addiction. A recent study has focused on validating an adapted version of the ESTUDES scale, specifically designed to measure substance consumption and risk perception among young athletes, aiming to provide a robust tool for preventative interventions.

The study, conducted as a descriptive cross-sectional survey, involved 914 adolescent footballers and futsal players from Jaén and Granada, Spain, aged between 12 and 18 years. Researchers utilized an adapted ESTUDES 2023 questionnaire, comprising 20 items that assess tobacco, alcohol, cannabis consumption, and gambling behaviors, alongside their associated risk perceptions. Through rigorous exploratory and confirmatory factor analysis, the study identified five distinct factors that collectively explain a substantial 73.47% of the variance in the data. These factors were categorized as tobacco use, alcohol use, gambling, cannabis use, and risk perceptions.

The findings revealed adequate reliability for the scale, with a Cronbach’s alpha of 0.863, and satisfactory model fit indices, including a Comparative Fit Index (CFI) of 0.920 and a Root Mean Square Error of Approximation (RMSEA) of 0.060. Notably, the study found significant correlations between different types of consumption, with the strongest positive association observed between tobacco and alcohol use (0.564). Conversely, risk perceptions exhibited negative relationships with all forms of consumption, suggesting that a heightened awareness of potential harms is linked to reduced engagement in addictive behaviors.

This validation process underscores the scale’s utility as a valuable instrument for assessing addictive behaviors and informing the design of targeted prevention programs specifically for adolescent athletes.

The Critical Role of Organized Sport in Adolescent Development

Organized sport offers a structured environment that transcends mere physical activity, contributing significantly to a higher quality of life and enhanced psychological well-being for adolescents. Beyond the physical benefits, participation in sports cultivates crucial interpersonal skills, such as improved socialization and the breaking down of stereotypes, particularly within inclusive settings for individuals with disabilities. On an intrapersonal level, sports participation is strongly linked to the development of emotional regulation, a cornerstone for navigating the complexities of adolescence. These abilities are vital for adolescents as they confront daily stressors, including academic pressures and future career uncertainties, while simultaneously navigating the developmental stage characterized by increasing autonomy. The cultivation of self-efficacy and personal resilience, fostered through sport, empowers young individuals to effectively manage adverse events and mitigate the rise in mental health challenges often associated with such pressures.

The neurological underpinnings of these benefits are significant. Physical activity, as observed in organized sports, induces neuroplasticity, optimizing stress reactivity and buffering the impact of stressful experiences. This is particularly critical during adolescence, a period of heightened vulnerability and brain development. The ability to balance immediate desires with long-term collective benefits, as conceptualized by theorists like Bauman, is directly influenced by the development of these emotional regulation skills.

Addressing Adolescent Addiction: A Public Health Imperative

In contemporary society, the prioritization of universal prevention strategies to curb substance abuse and behavioral addictions among youth has become a key focus of public health policy. Developing personal, social, and contextual skills is recognized as a priority objective for reducing vulnerability to drug use and other addictive behaviors. Simultaneously, promoting healthy lifestyles and leisure alternatives that are incompatible with substance abuse is essential. This study aligns with these public health goals by examining the influence of sports participation and healthy leisure alternatives on addiction, employing the ESTUDES framework. The research aims to provide a descriptive overview of addictive consumption patterns among adolescent athletes and contribute to the ongoing discourse on effective prevention programs for addictive behaviors.

The ESTUDES survey, originally designed for use in educational settings with adolescents aged 14-18, has been adapted for this study to cater to younger athletes (12 years and older) and the specific context of sports. The original ESTUDES questionnaire, as described by the Ministry of Health, comprises 34 items assessing consumption patterns (age of onset, lifetime, annual, and monthly frequency) and risk perception regarding various addictive behaviors. Unlike clinical screening tools such as the AUDIT questionnaire, which are designed for specific clinical assessments, the ESTUDES scale is intended for broader monitoring and contextualized analysis. This approach is informed by theories like Bandura’s social learning theory, which highlights the influence of social factors, such as peer pressure within sports teams and team culture, on adolescent consumption patterns.

Adolescence is a critical period for the potential development of addictive behaviors, which can lead to severe personal consequences, including mortality, dependence, and the erosion of relationships. The neurobiological impact of persistent addictive behaviors is also a significant concern, as they can alter brain receptors and processing, affecting cognitive functions and potentially contributing to conditions like epilepsy and Alzheimer’s disease. Therefore, the primary objective of this study was to validate a robust instrument capable of accurately measuring consumption and risk perception related to addiction in young individuals within protective environments like sports. A secondary objective was to facilitate informed decision-making for the development of specialized prevention programs within sports contexts, providing a concise, rigorous, and comparable assessment tool.

Methodology: A Deep Dive into the Study Design

This research employed a descriptive, exploratory, and cross-sectional design to investigate addictive consumption and risk perception among adolescent athletes. The study recruited a sample of 914 adolescent football and futsal players from Andalusia, Spain, with participants drawn from Jaén capital (28%), Granada capital (45.6%), and the province of Granada (26.4%). The age distribution of the sample was segmented into under-13s (33.3%, aged 12-13 years), under-15s (39.3%, aged 14-15 years), and under-18s (26.9%, aged 16-18 years).

Socioeconomic and demographic data provided further context for the sample. The majority of participants came from families with at least one employed parent. Mothers reported a higher level of university education compared to fathers (40.8% vs. 35.6%). In terms of perceived economic status, most participants (82.9%) felt their financial situation was comparable to their peers. Leisure spending habits showed a U-shaped distribution, with common amounts for going out being €0-5 (28.7%) and over €15 (21.9%).

The study adhered to stringent ethical guidelines, securing a favorable opinion from the Human Research Committee of the University of Granada (No. 4968/CEIH/2025) and complying with the ethical principles outlined in the Declaration of Helsinki.

Instrument Design and Adaptation

The core of this research utilized the ESTUDES 2023 questionnaire, a standardized instrument widely used in Spain and comparable to similar surveys conducted internationally. This questionnaire is structured into various modules, which have been progressively expanded over the years. For this study, two key modules were selected:

1. Basic Module: This module collects sociodemographic data, family information, leisure habits, and consumption patterns of alcohol, tobacco, and cannabis. Crucially, it also assesses the perception of risk associated with addictive behaviors. These substances were chosen due to their prevalence and documented empirical presence within adolescent athletic populations.
2. Gambling Module (added in 2014): Questions related to gambling behavior were integrated into the study, mirroring the format used for alcohol, tobacco, and cannabis consumption.

Other modules of the ESTUDES survey were excluded as their relevance and prevalence within structured sports contexts were deemed insufficiently established for this initial validation study.

Data Collection Procedure

A multi-stage sampling approach was employed to recruit participants. Clubs were randomly selected, followed by the teams within those clubs. All available players from selected teams were invited to participate. Prior to data collection, an information document was distributed, detailing the study’s objectives, the commitment to share overall results, and assurances of confidentiality and anonymity.

Following authorization from club management or youth team coordinators, informed consent was obtained from the legal guardians of potential participants. The questionnaires were administered over the last four months of 2024. Researchers were present during administration to ensure correct completion and address any queries, with coaches also present to facilitate the process. Data collection occurred under normal conditions without significant incidents. Participant anonymity was rigorously maintained throughout the entire procedure.

Statistical Analysis Techniques

The study employed a combination of statistical software, IBM SPSS® version 22.0 and JASP 0.95.4, for data analysis. Exploratory Factor Analysis (EFA) was conducted using the maximum likelihood method with varimax rotation, excluding factor loadings below 0.4. Internal consistency of the scale was assessed using Cronbach’s alpha, with a 95% reliability index.

Confirmatory Factor Analysis (CFA) was utilized to further validate the scale’s structure, employing goodness-of-fit indices and Chi-square tests. Given that the variables were ordinal and not normally distributed, the diagonalized weighted least squares (DWLS) adjustment function was applied to prevent kurtosis from affecting standard errors.

To evaluate the adequacy of the data for factor analysis, the Kaiser-Meyer-Olkin (KMO) measure was calculated, with values above 0.80 considered satisfactory. Model fit was assessed using several indices: Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), Comparative Fit Index (CFI), Normalized Fit Index (NFI), and Incremental Fit Index (IFI). Criteria for a good fit were set as RMSEA < 0.06, SRMR < 0.08, CFI > 0.95, and TLI > 0.95.

Key Findings: Unpacking the Data

The study’s results, detailed in Table 1, provide a comprehensive overview of the 20 items comprising the adapted addictive consumption scale. The questionnaire’s structure and dimensions were derived from the ESTUDES survey’s core module and the 2014 gambling module, forming an abbreviated version.

Subsequent to descriptive analysis, a sedimentation graph was generated to determine the optimal number of factors. Kaiser’s criterion (eigenvalues greater than 1) and the "elbow" criterion (inflection point of the curve) were applied. The graph indicated that the first component had a significantly higher eigenvalue than the others, followed by a sharp decline. An "elbow" was observed between the fourth and fifth components, suggesting a five-factor solution.

Table 2 presents the psychometric properties of the ESTUDES questionnaire, focusing on the 16 items related to consumption of major addictive substances. An exploratory factor analysis, using principal components and varimax rotation, yielded five factors that collectively accounted for 73.47% of the total variance. The factor loadings, eigenvalues, and explained variance for each factor are detailed in the table.

The correlation matrix demonstrated adequacy, with Bartlett’s statistic showing a good fit ([14685.749; gl=190; p<0.001]), indicating that the variables were sufficiently related for factor extraction. The Kaiser-Meyer-Olkin (KMO) index value was 0.811, further supporting the suitability of the data for EFA. The determinant of the matrix (|R| = 0.00000009046) confirmed the invertibility of the matrix and the presence of sufficient relationships between variables to avoid complete collinearity.

Interpretation of Factors

The EFA identified five factors, explaining 73.47% of the total variance, a substantial portion considered adequate in social sciences. These factors were interpreted as follows:

• Factor 1: Tobacco Use: This factor encompasses items related to the age of onset and frequency of tobacco use (lifetime, last 12 months, and last 30 days).
• Factor 2: Gambling: This factor includes items concerning the age of onset and frequency of gambling across different timeframes.
• Factor 3: Alcohol Use: Similar to Factor 1, this factor groups items on the age of onset and frequency of alcohol consumption.
• Factor 4: Cannabis Use: This factor includes items on the frequency of cannabis use, with the age of onset item excluded due to a factor loading below 0.4.
• Factor 5: Risk Perceptions in Addictive Behaviors: This factor comprises four items assessing the perceived social and health dangers associated with different levels of tobacco and alcohol consumption.

Reliability indices for most dimensions were satisfactory. Factor 2 (Gambling) demonstrated the highest internal consistency (α=0.890), followed closely by Factor 1 (Tobacco Use) (α=0.881) and Factor 3 (Alcohol Use) (α=0.879). Factor 4 (Cannabis Use) also showed adequate values (α=0.849), while Factor 5 (Risk Perceptions) had slightly lower but acceptable reliability (α=0.648). The overall scale achieved a reliable Cronbach’s alpha of 0.863.

Confirmatory Factor Analysis and Inter-Factor Correlations

A confirmatory factor analysis (CFA) was conducted to corroborate the EFA findings. The structural equation model, comprising five factors and 19 observed variables, yielded a significant chi-square value (χ²=610.752; df=142; p<0.001). However, acknowledging the sensitivity of the chi-square statistic to sample size, other fit indices were examined. The CFI and IFI were 0.920, NFI was 0.900, and TLI was 0.904, indicating near-acceptable values. The RMSEA was 0.060, and SRMR was 0.059, both considered adequate.

Table 3 details the standardized factor loadings from the CFA. Fifteen variables exhibited high loadings (>0.7), and four showed moderate-to-high loadings (0.5-0.7), with all achieving statistical significance (p<0.001).

The standardized covariance values between factors revealed statistically significant relationships (p<0.001), indicating an integrated and consistent factor structure. The strongest positive correlation (0.564) was between tobacco use (Factor 1) and alcohol use (Factor 3), aligning with the known comorbidity of these substances. The lowest positive correlation (0.323) was between alcohol consumption (Factor 3) and cannabis consumption (Factor 4), potentially reflecting differentiated consumption patterns.

A significant finding was the negative correlation between Factor 5 (risk perceptions) and the consumption factors. The most pronounced negative correlations were observed with alcohol consumption (-0.227) and gambling (-0.152), suggesting that a higher perception of risk is associated with lower engagement in these behaviors. This inverse relationship between risk perception and actual consumption is a crucial insight for prevention strategies.

A visual representation of the structural model confirmed the robustness of the five-factor model, with item loadings consistent with previous findings and inter-factor correlations aligning with existing literature on adolescent addiction and risk perception.

Discussion: Implications and Future Directions

This research successfully validated a scale for measuring consumption and risk perception related to tobacco, alcohol, and cannabis among adolescent athletes, utilizing both exploratory and confirmatory factor analysis. The scale’s significance lies in its ability to provide a valid and reliable instrument for comprehensive comparisons of adolescent addictive consumption across different contexts. By adapting a tool originally designed for school-aged adolescents (14-18 years) to include younger athletes (from 12 years) and the specific sporting environment, the study addresses a notable gap in existing health, educational, and social research.

The identified five-factor structure, supported by robust statistical indicators such as KMO, Bartlett’s test, and high Cronbach’s alpha values, demonstrates the model’s strength. The total variance explained, exceeding 50%, further reinforces the model’s robustness. Theoretically, the dimensions are thematically coherent: "tobacco use," "gambling," "alcohol use," and "cannabis use" capture distinct substance and behavioral dependencies, while "perceptions of risk in addictive behaviors" addresses the cognitive aspect of harm awareness.

While the "risk perceptions" factor exhibited slightly lower internal consistency (α=0.648), it remains within an acceptable range for exploratory instruments. The study acknowledges that four items may not fully encompass the multidimensional nature of risk perception, suggesting that future iterations could benefit from additional items to enhance this dimension.

The confirmatory factor analysis validated the five-factor structure, with high factor loadings and statistical significance across all items. The model fit indices, while showing a significant chi-square value (a common occurrence with large sample sizes), were otherwise within acceptable ranges, affirming structural consistency.

The significant correlations between factors, particularly the strong positive association between tobacco, alcohol, and gambling, highlight the propensity for poly-consumption among young individuals with addictive tendencies. This underscores the importance of comprehensive prevention strategies that address multiple addictive behaviors to prevent a potential gateway effect to more severe substance use. The negative correlation between risk perception and consumption patterns is a critical finding, suggesting that enhancing awareness of potential harms can serve as a protective factor.

It is important to acknowledge potential limitations, such as memory recall issues or social desirability bias that might influence responses related to lifetime frequency of addictive behaviors and sociodemographic data. These are inherent challenges in survey-based research.

Conclusion: A Validated Tool for Prevention

The developed scale for measuring addictive consumption in young athletes has demonstrated adequate structural validity and internal consistency through rigorous exploratory and confirmatory factor analysis. The refined five-factor model, encompassing tobacco use, alcohol use, gambling, cannabis use, and risk perceptions in addictive behaviors, offers a coherent and comprehensive evaluation of these constructs.

The goodness-of-fit indices from the confirmatory model, coupled with the standardized factor loadings, confirm the instrument’s robustness and utility in identifying consumption patterns among adolescent athletes. The identified factor structure aligns with established theories on the development of addictive behaviors in young people, providing a valuable profile for educational and policy considerations within regional regulations and initiatives.

The scale’s brevity, conceptual clarity, and comparability with national reports make it an accessible and effective tool for implementation in youth settings and prevention programs. Its application can aid in identifying prevalent addictive behaviors in sports and evaluating the effectiveness of selective interventions targeting athletes. Future research should focus on validating this scale across larger and more diverse samples and exploring its relationship with external variables such as mental health, family dynamics, and peer relationships. This continued validation and application will be crucial in fostering healthier environments for young athletes and mitigating the risks associated with addiction.