2. Materials and Methods
We conducted a preliminary descriptive analysis based on the premise of a generalized linear regression model with logical functions linked to it. For analysis and collection of data, we created a survey with questions based on previous investigations [
40], whose construct and content validity were assessed by experts [
41]. The questions were structured through a 5-to-7-item Likert scale, and, subsequently, the most relevant variables were selected, some of which were standardized and grouped for exploratory factor analysis. In any case, reliability between variables was measured using Cohen’s Kappa coefficient, resulting in K = 1 in all the variables.
To establish our research we created an 18-item online questionnaire that was distributed from 10 October 2020 to 20 March 2021 among the students of public universities in Madrid, being the universe comprised of 196,823 people, hence generating an effective sample (ES) of 1032 individuals, with a 95% confidence level and a margin of error of 3.04%. All ethical aspects were taken into account when conducting this research. The selection of people was carried out in the different faculties by distributing a QR code with which the study could be accessed. Informed consent was presented at the beginning of the survey conducted through Google Forms to preserve the anonymity of the sample.
The minimum age of the sample collected was 17 years old and the mean age was 18.9 years of age. The gender distribution was 57% women (n = 588) and 43% men (n = 444). The quantitative research stage entails a series of steps that involve explaining in detail the statistical analysis that determines the methodology used in this investigation. IBM SPSS v.25 software (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.) program was used to analyze the data collected. After cleaning the variables, we explored the correlations between variables to know if they shared a latent structure. After the variables were standardized, we proceeded to the reduction of factors and to implement the KMO test to establish the suitability for factor analysis, evaluating the existing correlation between the variables and the existence of a latent structure between them. Similarly, Bartlett’s test of sphericity was used to analyze the applicability of factor analysis to the chosen variables. Cronbach’s alpha was implemented to assure the verification of the research tool’s effectiveness [
42].
3. Results
The analysis of the results links the variables that articulated the research questions with all the aspects related to online gambling, the presence of tipsters, and their influence. Regarding RQ1, the presence of online sports gambling in the life of young people, the total corpus was distributed in 59.4% (613) who had gambled on online sports betting sites in the past 12 months and 40.6% (419) who had not done so. To complete the analysis of the remaining items in the questionnaire, we proceeded to filter the sample to obtain only the data of the active users in online sports gambling. To address RQ1 in a comprehensive manner, we proceeded to analyze the correlations between this first question and the other two related aspects, namely the frequency of bets being placed and the amount of money available (See
Table 1).
The correlations observed above show that the questions inquiring about the presence of online sports gambling in the life of young people have a p-value lower than 0.05, which means they are statistically significant. All the correlations are positive, and the correlation with the lowest value (0.632) has a very strong relationship between “participation in online gambling” and “amount of money available”. The highest value (0.830) also shows a very strong relationship between the frequency of bets being placed and the amount of money available.
After studying the variables regarding RQ1, all those variables alluding to RQ2 were analyzed, meaning tipsters’ level of knowledge and their influence on the bets that young people place. Just like the previous table, we proceeded to study their correlations by applying Pearson’s correlation coefficient (See
Table 2).
Again, the level of significance indicated that the correlation between variables was significant and positive. The lowest value in this new analysis (0.711) already shows a very strong correlation between following tipsters and the bets being placed due to the tips given by these types of influencers. The highest result (0.917) shows a very strong correlation between the bets being placed due to the tips given by tipsters and the fact of more money being wagered after receiving their recommendations.
The last step in this part of our research established some final correlations between those variables concerning RQ3, that is, the relationship between tipsters and addiction to online sports gambling (See
Table 3).
In this case, the results show that the correlations are significant and positive. The correlation is very strong only in the relationship between the knowledge of friends being addicted to online sports gambling and tipsters’ influence on them (0.818). However, the correlation is weak or moderate in the remaining correlations, and there is only one strong correlation left (0.374), the relationship between subjects’ perception of their own addiction to online sports gambling and the influence that tipsters exert on their bets.
Subsequently, we conducted the KMO test, and, since it was very close to 1, the Kaiser–Meyer–Olkin measure of sampling adequacy indicated a strong relationship between the variables. Similarly, Bartlett’s test of sphericity was conducted, resulting in a value lower than 0.05, thus indicating the suitability of data for exploratory factor analysis (EFA) (See
Table 4).
The total explained variance, grouped into two factors, only explained 43.75% of the variance, while being grouped into three factors raised it to 77.8%. The extraction of the rotated component matrix agglutinated the variables in a similar way as they had been observed in the high and very high correlations (See
Table 5).
With the Cronbach’s alpha test being standardized, we verified that the correlations between the constructs were reliable. Since they are higher than 0.600, their validation can be asserted. The factors were labeled as Gambling, Tipsters, and Addiction (See
Table 6).
After standardizing the variables and grouping them into the three factors, we chose and specifically calculated the Person’s correlation coefficient and Spearman’s correlation coefficient, with a significance level set to 0.05 (See
Table 7).
After observing the table, we can note that the strongest existing relationships between variables correspond to those concerning tipsters, both regarding their influence when it comes to placing bets and their role when it comes to this habit becoming an addiction (r = 0.731). The correlation is very strong and positive, meaning that the higher the influence of tipsters on gambling is, the more they are regarded to have an influence on creating addicts.
There are also strong and positive correlations between young people who gamble and the influence that tipsters exert on them (r = 0.643). The last aspect studied in this analysis also relates gambling to addiction (r = 0.602). After confirming all these aspects through Pearson’s Correlation, we conducted a confirmatory analysis of the study through Spearman’s Correlation (See
Table 8).
It can be observed that the ranks between variables underpin the ones previously obtained through Pearson’s correlation. In fact, the correlation between tipsters and addiction (rho = 0.722) and the correlation between gambling and addiction (rho = 0.705) confirm that there is a relationship between them, just as aforementioned. Similarly, the strong correlation between the variables gambling and tipsters can be noted, with a p-value equal to absolute zero, and rho = 0.703.
4. Discussion
This research relates the figure of influencers on online sports betting, tipsters, to the action of placing bets and the possible risk of transitioning to an addiction such as problem gambling [
2,
7,
11,
12]. The objective is to know young people’s perception of the figure of tipsters and whether they think tipsters are generators of addictive behaviors, in this case, of gambling [
10,
13]. Gambling is legal, but its abuse may lead to a nonsubstance addiction, or even a disorder, as claimed by the World Health Organization [
43].
The results of the analysis show that gambling and the presence of tipsters are worthy of a thorough reflection. It is true that the world of gambling has been subjected to significant restrictions in its more traditional facet, such as casinos and slot machines. In fact, access was denied to minors in the case of places dedicated to gambling, and their presence in the media was practically inexistent [
7,
13]. Nevertheless, the appearance of online sports betting has entailed the rupture of that model, and advertisement for that mode of gambling has increased exponentially. It also led to the emergence of tipsters, as an example of persuasion on social networks, taking advantage of the fact that there are no specific laws to regulate commercial communication, neither in Spain nor in Europe [
10,
19].
However, the appearance of addictive behaviors related to these types of gambling among young people has caused important social consequences. This has promoted, in many countries, the initiation of regulatory processes, such as in Spain [
31]. The law of the Ministry of Consumer Affairs addresses especially the figure of tipsters and their modus operandi. It explicitly limits their actions, both in how they incite gambling and the accuracy of the data they provide.
The analysis of the three factors has shown high correlations, especially in the case of tipsters and addiction to online sports gambling. The importance of these data lies in the fact that these types of influencers hold, in their communications, enough attraction to cause young people to believe that they can lead someone (themselves or other people) to addictive behaviors [
11]. There are also important ethical considerations for tipsters regarding the psychological manipulation of people, leading them to pernicious habits [
19].
As for this study’s central subject, which analyzes young people’s perception of tipsters, the results reveal that there is a clear and positive (in statistical terms) relationship between gambling, tipsters, and addiction. This suggests that more bets are placed when tipsters intermediate these processes, and this can be explained according to Cialdini [
44] and the theory of decision making. It is worth considering that the more people follow their tips, the more probabilities there are of developing addiction. The high impact of tipsters on the bets that young people place and the fact of more bets being placed more frequently, with more money involved, cause young people to perceive that anyone could transition more easily to problem gambling [
18].
This research aimed to know young people’s perception of tipsters and whether these influencers could lead them to addiction, but after analyzing the results, we concur with the postulates of Perelló, Muela, and Romero [
45] regarding the particularly vulnerable publics in this area. The characteristics of the development period of the group of respondents allow us to refer to them as emerging adulthood [
46], and they are exposed to unregulated messages that could fit the concept of fake news, and yet, there is no dissuasive or punitive regulation concerning this aspect. Addiction to online sports gambling must be considered a public health issue, and it should not be addressed from the perspective of consumption alone. Similarly, other vulnerable publics, such as children, are exposed to these risks through the indiscriminate use of smartphones. In fact, the risk is not only limited to problem gambling since other disorders could be involved, in a direct way or as a consequence of gambling addiction [
47].
4.1. Implications
Previous works have already warned about tipsters’ behaviors and their influence capacity [
46]. Even their predictive capability has been studied, measuring its reliability and its connection with the flow of gambling markets [
47,
48]. In fact, there are also publications about the influence of tipsters on diagnosed problem gamblers [
49].
However, this research makes clear that the marriage of young people, gambling, and tipsters tends to lead to addiction, something that even the subjects of this study perceive. The Public Administration must consider banning the use of these types of influencers in the communication of online sports gambling. The limitations must extend to the level of other products, such as drugs, and glance over other fields, in which the use of influencers is generalized, such as the fashion industry [
50].
Bearing in mind that many of the bookmakers that use tipsters are not established in Spain, the legislation should not be limited only to the Spanish ambit, but it should extend to the European context. The European regulations must homogenize the national legislations to walk over one single path that prevents any type of technological constraint. Finally, it should be noted that scholars of the causes and consequences of addictions highlight the necessity of educating the public about personal control, resilience management, and emotional intelligence from an early age, interweaving educational curricular content and this cross-disciplinary content [
51], and synchronizing the new pedagogy to these goals [
52,
53,
54].
4.2. Limitations and Future Research
This study’s main limitation is that it is focused on demonstrating the correlation between gambling, tipsters, and addiction, while future works should delve into noteworthy variables such as segmentation by gender, age, or financial capacity. Another limitation is that the analysis does not distinguish what types of products tend to lead more to problem gambling (e.g., welcome bonus, multiple bet) or the moment of placing a bet (i.e., before the sporting event occurs or while it is taking place). Similarly, the collective or individual nature of bets or their amount will be the subject of study of future works.
The main focus of this research is young university students, but future investigations could widen the age band, both upwards and downwards, to cover segments completely, such as millennials, centennials, or Generation Z. Similarly, other Spanish regions could provide a more holistic vision of the country’s situation, and even an analysis at a European level can be conducted.
5. Conclusions
The use of tipsters in online sports gambling is experiencing an unprecedented boom, taking advantage of the current legal vacuum. The influence of these types of actors is perceived, by young people, as a factor that promotes addiction to these kinds of behaviors. The existence of tipsters is also justified from a perspective of supporting the placing of more bets and larger sums of money at stake.
Young people clearly perceive that the use of tipsters leads to these types of habits, which, either in them or other people, generate problem gambling. The trust in tipsters’ messages as well as the communication of data regarding gambling cause people to place sports bets online. Similarly, young people associate these factors with addiction as a direct consequence.