Prevalence of alcohol consumption among high school students: A cross-sectional study
Abstract
Aim
This study addresses the risk and protective factors for alcohol consumption among medical-technology high school students. The specific objectives of the study were to analyse standard influences on excessive alcohol consumption (influence of parents and upbringing) and possible modern influences, represented by social networks and internet use.
Design
A cross-sectional analysis.
Methods
The sample included the entire cohort of third-year students attending high school in Varaždin (n = 1,352). Data were collected using an anonymous questionnaire. The bivariate analysis used an independent t test and a Chi-squared test. The multivariate analysis used logistic regression. The study was conducted from September 2018 to February 2019.
Results
Alcohol consumption was most prevalent among vocational students, followed by college-preparatory students and medical-technology students. Style of parenting and maternal authority have a positive influence on less alcohol use among students. The results showed that smartphone ownership and internet use do not correlate with alcohol use among high school students.
1 INTRODUCTION
Alcohol is a psychoactive substance that causes dependence, producing a large public health burden among young people (Stockings et al., 2016). Alcohol consumption is the main cause of death and disease all around the world. It worsens brain function and increases the risk of death, injury, physical and sexual violence and many other social deviations (El Jilali et al., 2020; Kim et al., 2022).
Previous research indicates that drinking is socially acceptable on certain occasions throughout Europe. For example, the prevalent drinking pattern in the wine-producing countries of southern Europe is frequent consumption of moderate amounts of alcohol (Kuendig et al., 2008). Average consumption in central and eastern Europe (CEE) is high, with a relatively large proportion of annual unrecorded consumption of pure alcohol ranging from 1.0 L in the Czech Republic and Estonia to 10.5 L in Ukraine per capita (Popova et al., 2007). In CEE, alcohol use is the fourth-leading risk factor for disease and mortality (Forouzanfar et al., 2015).
Nurses must be aware of the dangers of young people drinking, recognize the signs of alcohol abuse and know how to intervene. Frequent drinking of alcohol leads to health damage, so nurses must assume an active role in health promotion and ensure that adolescents are aware of the associated dangers (Kiernan et al., 2012).
2 BACKGROUND
Risky and harmful use of alcohol is still the most important cause of death among young people between the ages of 15 and 29 (WHO, 2018). Risk factors for alcohol consumption are divided into two categories: the first category includes legal, social and cultural factors that provide a normative assumption for behaviour, and the second category is factors of individuals and their interpersonal environment (Petronytė et al., 2007). An Australian study carried out a decade ago emphasized the use of alcohol in the family, specific communication patterns (the extent to which adolescents feel free to talk to their parents about emotional topics), adopted rules and parental involvement, quality of the parent–child relationship, family conflicts and parental monitoring of adolescents' everyday activities (Ryan et al., 2010).
Studies also show that many parents take responsibility for young people's attitudes towards alcohol and their drinking habits (Ryan et al., 2011). Population studies find that early age of drinking onset correlates with increased lifetime risks for developing alcohol dependence, violence and injuries (Crews et al., 2016). Drinking during adolescence increases the risk of hazardous or harmful alcohol use, heavy episodic drinking, alcohol dependence, injuries and psychological distress (Pillai et al., 2014).
The Varaždin region has a reputation as an area with high alcohol consumption in Croatia. The most recent ESPAD (European School Survey Project on Alcohol and Other Drugs) survey showed that 64% of Croatian secondary school students had tried an alcoholic beverage before age 13. Furthermore, 11% had been intoxicated before age 13, which is higher than the European average (8%; ESPAD, 2015). In 2015, the study was conducted for the sixth time. Overall, 55% of Croatian students reported drinking alcohol in the previous 30 days. The results also showed that the prevalence of drunkenness reported in the previous 30 days was 16% for all students (17% for boys and 14% for girls; Kraus et al., 2016).
In Croatia, graduate nurses offer adolescents education, advice and information about the harm of alcohol consumption and abuse. They encourage the development of positive life habits and attitudes to avoid addiction (Moro & Frančišković, 2011). They also play an important role in educating and advising young people about the safe limits of drinking (Govier & Rees, 2013). However, parents and young people's social environments also play an important role in addressing alcohol misuse among adolescents (Ward & Verrinder, 2008). Studies show that supervision and good communication between parents and adolescents can delay the start of drinking (Koning et al., 2009).
A study of Japanese adolescents indicated that those that used the internet more consumed alcohol more often and in greater amounts compared to adolescents that used the internet less (Morioka et al., 2017). The authors linked this to insomnia and aggressive behaviour, which is related to more frequent drinking by students.
This study provides an overview of alcohol consumption among medical-technology (med-tech) high school students and formulates recommendations for the work of nurses conducting health education in schools in Varaždin County. The added value of this research is that, in addition to psychosocial factors, which also include family situations, it also investigated possible connections with electronic media use. The analysis was performed based on the type of school, and for the first time, it included students from med-tech high schools. The specific objectives of the study were to analyse standard influences on excessive alcohol consumption (influence of parents and upbringing) and possible modern influences, represented by social networks and internet use. These results will make it possible to plan the work of nurses involved in the health education of high school students in Croatia.
3 METHODS
3.1 Design and sample
A cross-sectional study design was created. The survey included 1,352 students from 13 high schools in Varaždin County during the 2018/19 school year. Their ages ranged from 15 to 20. There were 692 male students (51.2%) and 660 (48.8%) female students. The students were divided by type of school into college-preparatory (college-prep), vocational and med-tech students (future nurses, laboratory assistants, physiotherapists, etc.).
The entire third-year cohort was included in the study. The inclusion criteria were that the student was attending the third year and that he or she had signed an informed consent statement. Participation in the questionnaire was voluntary. The exclusion criteria were the following: the student did not sign a consent form, did not answer all the questions or gave up filling out the survey. If the questionnaire was not fully completed, it was not processed and used for analysis. Demographic variables were part of the questionnaire. Students answered questions about age, name of the school, sex and place of origin. Among psychosocial variables, students were asked to rate satisfaction with their life on a scale of 1 to 10 (1 = worst to 10 = best). Students were also asked how often they talk to their parents, and the kind of relationships they have with their mother and father was explored. When asked about their mothers and fathers, the students chose a statement about whether they are strict or lenient. A 5-point Likert scale was at their disposal. For the drinking habits of mothers and fathers, we asked whether the mother or father never drinks alcohol, drinks alcohol only on special occasions, occasionally drinks alcohol or often drinks alcohol.
The researcher JŠP scheduled the survey timing with the school principal or the teacher. For each class, she was given an appointment, and she gave the students surveys and informed consent forms. She was present the entire time the survey was being administered (45 min). The students returned the completed questionnaires to JŠP.
3.2 Measuring instrument and data collection
The data were collected using a questionnaire. Ajduković & Kolesarić, (2003) was fully respected throughout the entire process. The questionnaire was taken from and approved by Kolšek (2000). The current questionnaire was adapted and supplemented with questions on electronic media use. The questionnaire consisted of 59 questions. The students completed the paper version of the questionnaire during class time. They had 45 minutes to complete the questionnaire. They put their completed questionnaires in prepared envelopes and gave them to the researcher. The study was conducted from September 2018 to February 2019. The data were analysed from March to May 2019.
The primary dependent variable was the students' current drinking status. Students were asked to rate their satisfaction with their lives and what kind of relationship they have with their mothers and fathers. The electronic media variables included questions about smartphone ownership and internet use.
3.3 Ethical considerations
This study was approved by the Ethics Committee of the Ministry of Science and Education on 27 September 2018 (no. 533-05-18-004). No parental consent was required for the study; according to Ajduković & Kolesarić, (2003), in Croatia children, over the age of 14 may provide their own written or oral consent. The study was in accordance with the FRA's policy on child participation in research.1 Ajduković & Kolesarić, (2003) was fully respected in the written report.
3.4 Statistical analysis
Categorical data are represented by absolute and relative frequencies. Differences between categorical variables were tested using the chi-squared (χ2) test. The normality of the distribution of numerical variables was tested with the Shapiro–Wilk test. Numerical data are described with arithmetic means and standard deviations in the case of normal distributions and, in other cases, with medians and the limits of the interquartile range. Differences between normally distributed numerical variables between two independent groups were tested using the Mann–Whitney U test. Between the three independent groups, differences in numerical variables were tested with analysis of variance and, in the event of deviation from a normal distribution, with the Kruskal–Wallis test.
Logistic regression assessed the impact of multiple factors on the likelihood that students would consume alcohol. Ten independent variables (sex, school, satisfaction with family life, parental assistance, talking with parents, alcohol consumption with relatives, father's characteristics, mother's characteristics and each parent's alcohol consumption) were used, with the dependent variables being alcohol consumption and use of electronic media (owning a smartphone and internet use). The statistical program used was MedCalc Statistical Software version 18.11.3 (MedCalc Software, Ostend, Belgium) and SPSS Statistics 23 (IBM SPSS Statistics for Windows, Armonk, NY).
The overall reliability rating of the full scale is expressed using Cronbach's alpha. Cronbach's alpha for questions related to the parental relationship was 0.883. For the questions related to alcohol consumption, Cronbach's alpha was 0.305.
4 RESULTS
Students were divided by type of school into college-prep with 334 (24.7%) students, vocational with 803 (59.4%) and med-tech with 215 (15.9%). The median age of the students was 18 (interquartile range 17–18) with a range of 15–20. The results indicate that 92.4% of all students had tried alcoholic beverages. The highest percentage was in vocational schools (94%), followed by college-prep high schools (90%) and med-tech schools (89%). The median of alcoholic drinks consumed in the previous 30 days for all types of students was 10.
The interquartile ranges varied: for college-prep students, it ranged from 2 to 19, for vocational students 3 to 30 and for med-tech students 3 to 25. The median of alcoholic drinks consumed in the previous 7 days was two for college-prep students and three for both vocational and med-tech students. The interquartile range for college-prep students ranged from 0 to 5, for vocational students from 0 to 10 and for med-tech students from 0 to 5 (Table 1).
| Median (interquartile range) | p * | ||||
|---|---|---|---|---|---|
| College-prep | Vocational | Med-tech | Total | ||
| No. of alcoholic beverages drunk in the last 30 days | 10 (2–19) | 10 (3–30) | 10 (2–20) | 10 (3–25) | .001 |
| No. of alcoholic beverages drunk in the last 7 days | 2 (0–5) | 3 (0–10) | 3 (0–5) | 3 (0–7) | <.001 |
- * Kruskal–Wallis test.
Third-year students mostly drink beer (38.8%), followed by cocktails, white wine with sparkling water, rum and cola or alcohol in tea (18.6%), spirits (18.5%), wine or champagne (12.5%) and cider (3%); 8.7% do not drink alcohol at all (Table 2).
| Number (%) of students by type of school | p * | ||||
|---|---|---|---|---|---|
| College-prep | Vocational | Med-tech | Total | ||
| What type of alcoholic drinks do you drink most? | <.001 | ||||
| Beer | 99 (30) | 357 (44) | 68 (32) | 524 (38.8) | |
| Wine (including sparkling) | 38 (11) | 95 (12) | 36 (17) | 169 (12.5) | |
| Spirits (brandy, whiskey, liqueur, etc.) | 79 (24) | 134 (17) | 37 (17) | 250 (18.5) | |
| Cider | 14 (4.2) | 17 (2.1) | 9 (4.2) | 40 (3) | |
| Cocktails, white wine with water, rum-cola or alcohol in tea | 68 (20.4) | 137 (17.1) | 46 (21.4) | 251 (18.6) | |
| I do not drink alcohol at all | 36 (10.8) | 63 (7.8) | 19 (8.8) | 118 (8.7) | |
| Total | 334 (100) | 803 (100) | 215 (100) | 1,352 (100) | |
- * Chi-squared test.
Most often, students drink several times a month (41.4%). The highest number of students in this group are med-tech students (47%) and the lowest are vocational students (39%). Overall, 26.6% of students drink weekly; 30% of those attending vocational schools, 25% at med-tech schools and 19% at college-prep schools. A total of 18.6% drink a few times a year, 25% of whom are college-prep students, 17% vocational students and 15% med-tech students.
As many as 33.1% of students reported that when they drink alcohol they usually drink more than three drinks, 22.9% drink two to three drinks and 22.3% drink one to two drinks. As seen in Table 3, vocational students are most likely to drink more than three drinks (37.4%), med-tech students two to three drinks (27.9%) and college-prep students one to two drinks (27%).
| Number (%) of students by type of school | p * | ||||
|---|---|---|---|---|---|
| College-prep | Vocational | Med-tech | Total | ||
| Currently, I drink alcohol approximately | <.001 | ||||
| Several times a year | 84 (25) | 134 (17) | 33 (15) | 251 (18.6) | |
| Several times a month | 145 (43) | 315 (39) | 100 (47) | 560 (41.4) | |
| Several times a week | 63 (19) | 243 (30) | 53 (25) | 359 (26.6) | |
| Every day | 5 (1.5) | 41 (5.1) | 10 (4.7) | 56 (4.1) | |
| I do not drink alcohol at all | 37 (11.1) | 70 (8.7) | 19 (8.8) | 126 (9.3) | |
| When I drink alcohol, I usually drink | .002 | ||||
| Less than one drink | 8 (2) | 22 (3) | 7 (3) | 37 (2.7) | |
| One drink | 43 (13) | 72 (9) | 24 (11) | 139 (10.3) | |
| One to two drinks | 91 (27) | 162 (20) | 48 (22) | 301 (22.3) | |
| Two to three drinks | 65 (19.5) | 184 (22.9) | 60 (27.9) | 309 (22.9) | |
| More than three drinks | 90 (26.9) | 300 (37.4) | 57 (26.5) | 447 (33.1) | |
| I do not drink alcohol at all | 37 (11.1) | 63 (7.8) | 19 (8.8) | 119 (8.8) | |
| Total | 334 (100) | 803 (100) | 215 (100) | 1,352 (100) | |
- * Chi-squared test.
In terms of life satisfaction, in principle, all students are satisfied. Table 4 shows that among vocational students, 9% report that their parents talk to them never or rarely. Compared to other schools, a slightly smaller percentage (91.3%) of vocational students' parents sometimes or almost always talk to the students (med-tech schools 93.7%; college-prep schools 95.4%).
| College-prep | Vocational | Med-tech | Total | p | |
|---|---|---|---|---|---|
| How satisfied are you with your family life? Median (25%–75%) | 10 (8–10) | 9 (7–10) | 9 (7–10) | 9 (8–10) | .001† |
| My parents talk to me, n (%) | |||||
| Never | 4 (1) | 14 (2) | 2 (1) | 20 (1.5) | .02 * |
| Rarely | 10 (3) | 55 (7) | 11 (5) | 76 (5.6) | |
| Sometimes yes. Sometimes no | 175 (52) | 338 (42) | 106 (49) | 619 (45.8) | |
| Almost always | 145 (43.4) | 396 (49.3) | 96 (44.7) | 637 (47.1) | |
| Total | 334 (100) | 803 (100) | 215 (100) | 1,352 (100) | |
| My father is indulgent (1)–strict (5), mean (SD) | 3.77 (1.1) | 3.55 (1.1) | 3.62 (1.1) | 3.62 (1.2) | .02† |
| My mother is indulgent (1)–strict (5), mean (SD) | 3.94 (1.1) | 3.83 (1.1) | 3.61 (1.1) | 3.82 (1.1) | .003† |
| My father, n (%) | |||||
| Never drinks alcohol | 36 (11) | 92 (12) | 33 (17) | 161 (12.4) | .08* |
| Drinks alcohol only on special occasions | 138 (42) | 281 (36) | 62 (31) | 481 (36.9) | |
| Occasionally drinks alcohol | 124 (38) | 313 (40) | 87 (44) | 524 (40.2) | |
| Often drinks alcohol | 29 (8.9) | 90 (11.6) | 17 (8.5) | 136 (10.4) | |
| Total | 327 (100) | 776 (100) | 199 (100) | 1,302 (100) | |
| My mother, n (%) | |||||
| Never drinks alcohol | 83 (25) | 229 (29) | 67 (32) | 379 (28.5) | .006* |
| Drinks alcohol only on special occasions | 198 (60) | 400 (51) | 91 (43) | 689 (51.8) | |
| Occasionally drinks alcohol | 44 (13) | 146 (19) | 48 (23) | 238 (17.9) | |
| Often drinks alcohol | 6 (1.8) | 12 (1.5) | 6 (2.8) | 24 (1.8) | |
| Total | 331 (100) | 787 (100) | 212 (100) | 1,330 (100) | |
- Abbreviation: SD, standard deviation.
- * Kruskal–Wallis test.
- † Chi-squared test.
There is no statistically significant difference by type of school and father's alcohol consumption. A total of 42% of college-prep students’ fathers drink alcoholic beverages only on special occasions, whereas 44% of med-tech students’ fathers occasionally drink alcoholic beverages. There was a statistically significant difference depending on the type of school and how the mother drinks alcohol (p = .006, χ2 test). Most often the mothers drink only on special occasions (51.8%). Among mothers of med-tech high school students, 32% never drink alcohol. Mothers of college-prep students drink only on special occasions (60%).
Logistic regression assessed the impact of multiple factors on the likelihood that students would try alcohol. The model contains eight independent variables (sex, school, satisfaction with family life, conversation with parents, father's characteristics, mother's characteristics and each parent's alcohol consumption). The significance of individual predictors in predicting alcohol consumption is shown in Table 5.
| Parameter | β | Standard error | Wald | p | Odds ratio (exp β) | 95% CI for exp β |
|---|---|---|---|---|---|---|
| Male | 0.46 | 0.208 | 4.77 | .03 | 1.58 | 1.05–2.37 |
| School | ||||||
| College-prep | −0.03 | 0.32 | 0.010 | .97 | 1.05 | 0.60–1.78 |
| Vocational | 0.67 | 0.24 | 8.31 | .004 | 1.97 | 1.24–3.13 |
| Med-tech | −0.02 | 0.28 | 0.007 | .94 | 0.98 | 0.56–1.70 |
| Satisfaction with your family life | −0.14 | 0.07 | 4.32 | .04 | 0.87 | 0.76–0.99 |
| My parents talk to me | ||||||
| Rarely | 1.5 | 0.76 | 3.92 | .05 | 4.5 | 1.02–19.93 |
| Sometimes yes, sometimes no | 1.4 | 0.58 | 6.2 | .02 | 4.3 | 1.36–13.6 |
| Almost always | 0.85 | 0.57 | 2.2 | .14 | 2.4 | 0.76–7.28 |
| My father is | ||||||
| Unkind–kind | −0.08 | 0.26 | 0.10 | .75 | 0.92 | 0.56–1.53 |
| Hesitant–determined | −0.26 | 0.28 | 1.01 | .32 | 0.76 | 0.45–1.29 |
| Careless–diligent | −0.01 | 0.25 | 0.001 | .97 | 0.99 | 0.61–1.61 |
| Not interested in me–interested in me | 0.11 | 0.24 | 0.24 | .62 | 1.12 | 0.71–1.78 |
| Does not love me–loves me | 0.15 | 0.24 | 0.36 | .55 | 1.16 | 0.72–1.86 |
| Nervous–calm | −0.38 | 0.20 | 3.75 | .05 | 0.68 | 0.46–1.005 |
| Indulgent–strict | −0.46 | 0.12 | 14.4 | <.001 | 0.93 | 0.55–1.59 |
| Unfair–fair | −0.01 | 0.20 | 0.005 | .95 | 0.98 | 0.50–0.79 |
| Rough–gentle | −0.185 | 0.19 | 0.92 | .34 | 0.83 | 0.67–1.46 |
| My father consumes alcohol | ||||||
| Sometimes | 1.20 | 0.26 | 22.03 | <.001 | 3.33 | 2.02–5.51 |
| Rarely | 1.95 | 0.29 | 42.79 | <.001 | 7.0 | 3.91–12.54 |
| Often | 1.79 | 0.46 | 15.28 | <.001 | 6.02 | 2.45–14.80 |
| Constant | 3.864 | 12.114 | 0.102 | .750 | 47.669 | 0.979–1.044 |
| My mother consumes alcohol | ||||||
| Sometimes | 0.38 | 0.22 | 2.92 | .09 | 1.47 | 0.95–2.27 |
| Rarely | 1.07 | 0.38 | 7.96 | .005 | 2.92 | 1.39–6.14 |
| Often | 0.23 | 0.76 | 0.09 | .76 | 1.26 | 0.29–5.57 |
| My mother is | ||||||
| Unkind–kind | −0.75 | 0.32 | 5.35 | .02 | 0.47 | 0.025–0.89 |
| Hesitant–determined | 0.57 | 0.24 | 5.61 | .02 | 1.78 | 1.10–2.89 |
| Careless–diligent | 0.22 | 0.28 | 0.62 | .43 | 1.25 | 0.72–2.17 |
| Not interested in me–interested in me | 0.36 | 0.30 | 1.39 | .24 | 1.43 | 0.79–2.58 |
| Does not love me–loves me | 0.07 | 0.29 | 0.06 | .80 | 1.07 | 0.61–1.88 |
| Nervous–calm | −0.43 | 0.22 | 3.99 | .05 | 0.65 | 0.42–0.99 |
| Indulgent–strict | −0.64 | 0.14 | 21.33 | <.001 | 0.53 | 0.40–0.69 |
| Unfair–fair | −0.18 | 0.25 | 0.52 | .47 | 0.83 | 0.51–1.37 |
| Rough–gentle | −0.08 | 0.28 | 0.09 | .77 | 0.92 | 0.54–1.58 |
| Impact of internet use on drinking habits | ||||
|---|---|---|---|---|
| Number (%) of students according to whether they have ever tried alcohol | p * | |||
| No | Yes | Total | ||
| Do they own a smartphone | .06 | |||
| Yes | 97 (94.2) | 1,217 (97.4) | 1,314 (97.2) | |
| No | 6 (5.8) | 32 (2.6) | 38 (2.8) | |
| Do they use the internet | .09 | |||
| Yes | 99 (96.1) | 1,229 (98.4) | 1,328 (98.2) | |
| No | 4 (3.9) | 20 (1.6) | 24 (1.8) | |
| Total | 403 (100) | 400 (100) | 803 (100) | |
- * χ2 test.
Predictors that are significant were viewed as a model. The model was statistically significant overall, χ2 = 24.78, p = .002, indicating that it can distinguish students who drink from those who do not drink. The model as a whole explains between 8.1% (Cox & Snell) and 19.6% (Nagelkerke) of the variance among students who consume alcohol, and it accurately classifies 92.5% of the cases.
Only four independent predictors made unique statistically significant contributions to the model. If the student's parents are stricter and more determined, the student will be less likely to consume alcohol. Moreover, the strongest predictor that affects students’ alcohol consumption is their father's alcohol consumption (rare vs. frequent).
The correlation between alcohol and electronic media proved to be weak or non-existent. There was no correlation between whether students have ever tried alcohol and owning a smartphone (p = .06) or using the internet (p = .09).
5 DISCUSSION
The study results show that the share of alcohol consumption is high among med-tech students in Varaždin County, which was surprising because they include future health workers. Tejedor-Cabrera and Cauli found that most of the nursing students surveyed reported regular alcohol intake, with one-third being classified as having risky alcohol use, and one-fifth met the criterion for hazardous drinking based on the AUDIT score (Tejedor-Cabrera & Cauli, 2019)
Early identification of risk factors for adolescents can help prevent and/or reduce their risk (Marshall, 2014). Alcohol consumption by young people (particularly early initiation) is a predictor for poorer health in later life (Bowden et al., 2017).
Contrary to the findings of some other researchers (Morioka et al., 2017), we did not conclude in our study that smartphone ownership and internet use correlate with alcohol use among the high school students in our study. We expected to find links regarding the use of electronic media, but the results showed that there was no connection between whether students had ever tried alcohol and owning a smartphone or using the internet. Therefore, the potential effect of digitization in future research will need to be taken as a contextualization and not as an independent variable.
The most troubling finding of our study is that the share of alcohol consumption is also high among med-tech students. The reason for this may be that at the beginning of school, these students do not differ much from those at other schools; they follow their friends and are curious. It seems that with further education and real-life examples, they see that, in practice, they actually become more aware of the harm and negative effect of alcohol on health. More than 90% of med-tech school students from Varaždin County have already tried alcoholic beverages. This is in line with the findings of researchers from other countries, where concerns about frequent and excessive alcohol abuse in young people are increasing. The average age at which young people start drinking alcohol in Europe is 12.5 years. Over the last decade, the amount of alcohol consumption among adolescents in the United Kingdom has increased (Moore et al., 2010). A higher frequency and higher amounts of alcohol consumption were found in students in the upper years of medical school compared to the first year (Pires et al., 2015). The stress level of nursing students varies during education. Stress among students can lead to depression and anxiety, but also increased consumption of alcohol and psychoactive drugs (Pulido-Criollo et al., 2018). This may be the reason for increased alcohol consumption among medical students. This study found that certain attitudes and characteristics of parents (if the mother and father are stricter and if the mother is more determined) indicate that the student is less likely to consume alcohol. The father's alcohol consumption is the most powerful factor in transferring similar habits to the child or student (rare vs. frequent), which is similar to our study. A study investigating the influence of exposure to parental drinking on children's perception of drinking shows that what children see in their parents can be transferred to them. There is evidence of intergenerational transmission of drinking behaviour at a very young age (Cook et al., 2022). Paternal alcohol consumption is associated with an increased risk of alcohol dependence and alcohol use disorders among offspring (Thor et al., 2022).
The data for Varaždin County are also comparable with data for the entire country. In 2015, Croatia saw a slight decrease in how accessible alcohol was too young people. The availability of alcohol is still very high, even though it is regulated by laws that prohibit the sale and service of alcohol to minors (Pejnović Franelić et al., 2016). The general problem is that students in Croatia know very little about the harmfulness of alcohol, given that the vast majority distinguish signs of intoxication, but not the harmful effects of long-term alcohol consumption (Železnik et al., 2015). ESPAD results for Croatia showed comparable results (ESPAD, 2015).
Another important finding that is also consistent with studies abroad is that students, despite various prevention programs, education and considerable efforts, still consume a lot of alcohol. Of particular concern is the fact that med-tech students also consume large amounts of alcohol, and they are expected to be an example to their peers. It is obvious that prevention programs in schools are not very successful.
The most relevant problem is that alcohol use in the area where this study took place is socially acceptable and is considered a fairly harmless means of relaxation. Our study shows that alcohol consumption is most dependent on the psychosocial factors in students' environments, mostly determined by their peers and the subculture they grow up in. If parents show that they are “strong” in decision-making and are a positive example to their children, it will certainly affect their alcohol consumption, and it is similar in other places around the world (Bowden et al., 2017).
6 LIMITATIONS
This study relies on students' self-perceptions of their drinking habits, and their subjective satisfaction with family life and relationships with parents. It would be more objective to observe them all the time and live with them, which would be difficult to do with such a large sample. It is assumed that full anonymity reduced this potential bias. The study predominantly focused on psychosocial predictors and did not include some other factors that may play a role in alcohol consumption among young people, including the media and advertising. Research conducted on adolescents aged 13–18 in Canada indicates that since social distancing began due to COVID-19, the frequency of alcohol consumption among adolescents has increased (Dumas et al., 2020). Because our research was carried out before the COVID-19 pandemic, the results may be different now.
7 CONCLUSION
Our study resulted in some interesting conclusions; namely, that the role of the family is still at the forefront regarding alcohol consumption among med-tech students in Varaždin County. We found that alcohol consumption is most dependent on the psychosocial factors in students' environments. If parents show that they are decisive and authoritative in decision-making and if they provide a non-drinking example to their children, it will certainly affect their lower alcohol consumption. The correlation between alcohol and electronic media proved to be weak or non-existent. There was no correlation between whether students have ever tried alcohol and owning a smartphone or using the internet.
In order to reduce alcohol abuse, methods that integrate several manners of health promotion should be combined. The most important thing is to build a healthy public policy in which nurses play a key role in informing adolescents, families and the wider community. Nurses can identify strategies to focus on reducing youth alcohol use between local authorities and schools, and they can play a role in alcohol action plans designed to improve adolescent health. Nurses play a key role in fostering collaboration between the health sector, the police, education, adolescents and parents (Ward & Verrinder, 2008). All nurses, regardless of their place of work, should play an active role in promoting the health of children and young people, and they must have the knowledge and skills necessary to counsel adolescents and parents about the physical and mental risks of underage alcohol consumption (Kiernan et al., 2012).
8 IMPLICATIONS FOR FUTURE RESEARCH
Our research focused more on psychosocial predictors and excluded some other factors that may play a role in alcohol consumption among young people, including the media, advertising and the area where they live.
Nurses should already be involved in primary prevention as educators, but by using real-world examples, they are likely to reach students much better. Educating parents is also essential because they are the starting point for student behaviour. Nurses should be more involved in health education in schools because with their knowledge, role and involvement in prevention programs, they can contribute to reducing alcohol consumption among students. It is important that students' attention be drawn to the negative effects of alcohol on their bodies and social lives. Young people should be made aware of these negative consequences, and that there are other interesting ways to have fun and relax.
AUTHOR CONTRIBUTIONS
The authors participated in the redesign of the questionnaire. JŠP and DRP completed the study writeup and data analysis. Data analysis was conducted by KK. The authors read and contributed substantially to the draft, and they approved the final manuscript.
ACKNOWLEDGEMENTS
The authors are very grateful to the students who took part in this study.
FUNDING INFORMATION
This research is part of a doctoral dissertation, and none of the authors has any financial benefit from it.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
ETHICS STATEMENT
This study was approved by the ethics committee of the Ministry of Science and Education of the Republic of Croatia on 27 September 27 2018 (no. 533-05-18-004). No parental consent was required for the study; according to the Code of Ethics for Research Involving Children, in Croatia, children over the age of 14 may give written or oral consent on their own behalf. The study was in accordance with the FRA's policy on child participation in research (available at https://fra.europa.eu/en/publication/2014/child-participation-research). Parents were verbally informed about the study. The Code of Ethics for Research involving Children was fully respected in the written report.
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DATA AVAILABILITY STATEMENT
Data available on request due to privacy/ethical restrictions.
