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Introduction
Since their inception, social media have significantly impacted the daily lives of people worldwide. Today, these platforms play a predominant role, especially in media, research, politics, and healthcare (Cruz et al., 2024), transforming how users continuously communicate (Arab and Díaz, 2015).
We are thus facing a digital revolution led by “metamedia” (Jensen, 2013), where new forms of interaction through images, videos, comments, and diverse content emerge daily (Rejman and Porada, 2022). This scenario fosters innovative modes of mass social interaction (Campos-Freire et al., 2016), consequently affecting the emotional and mental well-being of the population (Bashir and Bhat, 2016).
Children and adolescents, especially those belonging to the Alpha generation, are the most vulnerable and susceptible to the effects of these platforms, particularly their advertising strategies, as recent studies have elucidated (Carnelian-Tantra, 2022; Martínez-Estrella et al., 2023; Popa et al., 2023). Despite being born into a digital environment and demonstrating great proficiency in technology use and information consumption, their psychological behavior in this context shows greater excitability, irritability, and egocentrism (Danilova, 2022).
This highlights the need to study the possible effects of social media on this demographic group, as they represent the future of society. Indeed, social networking sites present new challenges in terms of entertainment, employment, and education (Wang, 2024), and the popularity of apps such as TikTok is rapidly growing among the youngest users (Shutsko, 2020).
In this context, the present research focuses on analyzing how generation Alpha, born between 2010 and 2025 (McCrindle, 2023), consumes audio-visual and advertising content on TikTok and how these messages can psychologically impact them. This work combines the analysis of youth advertising consumption and its psychological repercussions, contributing to scientific advancement concerning concerns about children’s use of social media in general (Bozzola et al., 2022) and TikTok in particular (Heng-Fung and Yuen-Wong, 2023). This approach advocates the creation of more ethical and healthy digital-social and commercial spaces that promote and respect the psychological wellbeing of future generations.
The success and popularity of TikTok
TikTok is a social media platform that was developed and launched in the international market by the Asian company ByteDance in 2017. Its technological structure integrates the apps Douyin and Musical.ly, which creatively simulate music videos generated by users (VizcaínoVerdú, 2024). From its foundation to 2024, TikTok has accumulated over 1.5 billion active users worldwide. This achievement makes the platform one of the fastest-growing apps within a relatively short period (Olcott, 2024).
TikTok presents itself as the leading tool for short-form videos, with content easily consumed by scrolling vertically through a smartphone (TikTok, n.d.). This trend confirms the current preference for “micro-films” (short films that do not exceed three minutes and can be as short as approximately 10 seconds) (Brisset, 2015). Moreover, this type of content is often preferred by new generations such as Z (Cortés-Quesada et al., 2022).
However, TikTok’s algorithmic recommendation system was essential to its success. This algorithm uses artificial intelligence and machine learning to analyze user behavior and personalize their experiences, showing content tailored to their preferences and consumption habits (Siles et al., 2022). In other words, the personalization mechanism not only increases the time users spend on the platform (Zeng et al., 2021), but also maximizes exposure to targeted advertising content, making it a powerful tool for ad insertion (Yudhistira and Muflichah, 2022).
Unlike other social networking sites, such as Instagram, owned by Meta, TikTok’s algorithm was not originally public and transparent. This has generated various controversies (Kosters and Gstrein, 2024). For instance, the app exhibits a pattern of hiding content from users who supposedly do not fit the standards of “hegemonic beauty”, thus invisibilizing overweight individuals (Harriger et al., 2023), people with lower economic status, or those with disabilities (Ionescu and Licu, 2023), marginalizing all users and communities (Delmonaco et al., 2024). Additionally, the app rewards users who create and share content for the first time, but penalizes them by hiding their digital production if they are not consistent (Quiroz, 2020).
Generally, TikTok boosts posts that generate more engagement (interactions, views, and other forms of audience interaction), regardless of whether their narrative is positive, negative, real, or contains morally and ethically questionable elements (racism, sexism, ableism, homophobia, etc.) (Bueno-Fernades and Campos-Pellanda, 2022). Nevertheless, this type of content seems to favor the snackable audio-visual consumption preferred by the youth population (CortésQuesada et al., 2023), whose effects are unavoidable.
The effect of TikTok on youth
Social media has facilitated some advantages, such as rapid communication, connection, and information dissemination among the global citizenry (Tan-Phat, 2024), but it also raises dissonance in their study and social impact. Analyzing the content offered by these platforms reveals the “era of emptiness”. This indicates that TikTok, like other platforms, accelerates life rhythms and reduces the ability to abstract or manage boredom among users (Blasco-Fontecilla, 2021).
The app has become the preferred social communication channel among the younger generation, in which they participate, exchange messages, and consume audio-visual content daily (Owens, 2024). Adolescents and young adults are becoming the most active content creators on this platform due to its easy system for gaining fame (Abidin, 2021).
However, some studies have emphasized that prolonged exposure to such content can affect users’ attention (Abidin, 2021) and negatively impact eyesight or the central nervous system in the long term (Moncada-Jiménez and Chacón-Araya, 2012). In other words, the constant use of TikTok and exposure to its fragmented content can adversely influence the physical and cognitive health of children due to its repetitive and often distressing nature as well as the uncontrolled dissemination of information and advertising (Turuna et al., 2024).
One of the main issues with TikTok is that younger audiences may struggle to discern between content harmful to their visual or mental health and beneficial or truthful content. As McCashin and Murphy (2022) pointed out, it is crucial for communication and mental health professionals to combine efforts to understand the consumption system and its potential effects (Montag et al., 2021). In recent years, there has been an increase in hostile messages on TikTok (SidorenkoBautista et al., 2021), including, among other content, fake news or malicious messages (GarcíaMarín and Salvat-Martinrey, 2022).
The detrimental effects of TikTok use are largely related to how users interact with the platform. These effects include patterns of addictive and uncontrolled consumption (Miao et al., 2023), the spread of misinformation (Alonso-López et al., 2021), and depressive tendencies (Montag and Markett, 2024). In addition, excessive use of TikTok has been linked to symptoms of depression, anxiety, and attention deficits (Zheluk et al., 2022).
In this context, advertising plays a significant role. Brands exploit the addictive nature of TikTok through explicit advertising messages and influencer marketing strategies to develop more personalized and targeted campaigns based on its opaque algorithmic recommendation system.
The prominence of advertising on TikTok
On TikTok, a platform characterized by its high interactivity and algorithmic personalization capabilities (Lu, 2024), advertising strategies have acquired new dimensions and marketing opportunities. The app’s focus on short-duration audio-visual content facilitates the implementation of marketing strategies aimed at fostering continuous engagement between users and brands (Babu et al., 2024).
In this environment, the use of short and dynamic videos allows brands to tell stories that capture generation Alpha’s attention in only a few seconds. These narratives can include customer testimonials, behind-the-scenes stories of products, and real-life usage examples that help humanize the brand and strengthen the emotional connection with this demographic (Clark and Melancon, 2013). Thus, young’s people ability to interact directly with this content through comments, likes, and shares further reinforces the bond with the brand and its socializing agents, the influencers (Lajnef, 2023; Zozaya-Durazo et al., 2022).
Another effective technique for brands is the implementation of challenges and hashtag-based campaigns (Toni and Mattia, 2021). These strategies encourage young users to participate proactively by creating their own content related to the brand, thereby amplifying its reach and generating a quasi-addictive sense of belonging (Miranda et al., 2023). These practices, based on the consistency of impact and adoption of youth vernaculars, promote greater loyalty and long-term engagement.
Hence, from a communicational and psychological dimension, it is crucial to consider the responsibility of all parties involved in disseminating such content, especially considering the impact that continued consumption can have on younger generations.
Objectives
To analyze the impact of advertising consumption by generation Alpha on TikTok from audio-visual and psychological perspectives, the research was organized according to the following objectives:
(O1) Conducting a comprehensive analysis of TikTok content targeting children, focusing on audio-visual elements.
(O2) Examining the presence of content segmentation by gender among children during TikTok consumption.
(O3) Identifying and categorizing advertising content aimed at children on TikTok.
(O4) Understanding the psychological effects of audio-visual and advertising content consumption in children.
Methodology
To conduct the analysis, we employed a mixed methodology that integrated both quantitative and qualitative analyses (Chaves-Moreno, 2018). In the initial phase, we analyzed the audiovisual content of TikTok using quantitative content analysis, which enabled us to extract numerical results aimed at identifying significant correlations (Abela, 2002). Subsequently, we presented these results to a group of psychological experts using the qualitative Delphi method (Fletcher and Marchildon, 2014) to assess the impact of this type of consumption on children’s everyday lives.
First stage: Content analysis from the perspective of the generation Alpha
To perform a quantitative content analysis, we created two ad hoc profiles on TikTok. We selected the minimum age allowed by the app in Spain at the time of analysis (February-March 2024) to create blank profiles for 14-year-olds (born in 2010). This was justified by aligning with the generation Alpha conception (McCrindle, 2023) and differentiating them by available gender at the time of creation (boy/girl).
Before starting data collection, we carried out a pre-test to validate the inter-coder reliability analysis. We randomly selected a sample of 25 videos from each researcher, who individually analyzed the same set. Additionally, we measured the level of inter-coder agreement using Cohen’s Kappa coefficient, resulting in k=1, p=<.001, indicating almost perfect agreement.
Based on the outlined objectives, we selected a series of nominal and open variables to deductively analyze the content offered to children on TikTok (Table 1). In this initial phase, we aimed to: (O1) study the audio-visual format of the content appearing on TikTok for generation Alpha; (O2) analyze whether there is a differentiated segmentation based on the gender of children on TikTok; and (O3) identify advertising within the content targeted at this demographic group.
Table 1 Selected variables for content analysis
| (O1) Audio-visual format | (O1/O2) Type of content | (O3) Nature of content | |||
|---|---|---|---|---|---|
| Category | Code | Category | Code | Category | Code |
| Type of shots | Extreme long shot, long shot, full shot, American shot, medium shot, medium closeup, close-up shot, multiple shots, no shot | Video duration | 5/10 s, 11/15 s, 16/20 s, 21/30 s, 31/40 s, 41/50 s, 51/60 s, + 1 min, 2 min, + 2 min, more than one part, timeless image carousel | Level of communicative formality | Formal verbal/nonverbal communication, informal verbal/nonverbal communication, mixed verbal/nonverbal communication, vulgar/aggressive communication |
| Theme of the video | Politics, humor, cinema, music, fashion and beauty, sports, tutorials, food, books, science, current news, automotive, lifestyle, dissemination, TV clips, information, education, dance, art and culture, travel, environment and sustainability, personal coaching, animals, languages, finance, photography and video, social claim, opinion, motivational, advertising, other | Performer | Children, adolescents, adults, elderly, animals and people, no people | ||
| Visual effects | Use effects, Do not use effects | Nature of content | Influencer advertising, original content (non-promotional), viral content (mimics trends), business advertising, media channel | ||
Source: Created by the authors.
Each researcher was assigned to either the girl or boy profile and accessed it individually and daily using the selected profiles, collecting and recording information based on pre-established variables in a spreadsheet. The procedure involved viewing videos from the “For You Page” (FYP) without any form of interaction, such as likes, shares, comments, or navigation to other videos, to prevent the activation of a deeper level of the recommendation algorithm. This analysis was limited to a maximum of 20 minutes per profile each day. The process was performed during February and March 2024, resulting in a sample of 500 videos.
Second stage: Delphi method with experts in psychology
We implemented the Delphi method in the second phase with experts in the field of psychology to understand the potential effects of consuming this type of content in children (O4). We designed a Spanish-language questionnaire adapted to the contextual research scenario of the researchers (see https://forms.office.com/e/eEfBxchggW) with 20 multiple-choice questions and dichotomous and open-ended rating scales.
After collecting data from this initial questionnaire, we developed a second form (see https://forms.office.com/e/VCqW4eG1ES ) with five questions focused on expert evaluation and consensus. It is important to note that all experts provided informed consent before participating in accordance with ethical standards.
To select participants for the panel, we considered three psychological activity domains in Spain relevant to the context of our researchers’ analysis: (1) educational-academic (university researchers and faculty), (2) general psychology (licensed psychologists), and (3) clinical experts in children and adolescent psychology. These participants were identified using nonprobabilistic convenience sampling as key informants for a qualitative study of Spanish medical and university directories (Tongco, 2007).
17 experts participated in the first questionnaire, whereas 12 participated in the second. Thus, we exclusively considered the responses of 12 participants. After configuring the panel, we applied the Expert Competence Coefficient (K) (Cabero-Almenara and Infante-Moro, 2014), which encompasses three scenarios (see Table 2):
The K must be greater than 0.8 to be part of the expert panel.
The result of the Knowledge Coefficient (Kc) (knowledge of the subject matter) should be represented on a scale of 0 to 10, and the result should be multiplied by 0.1.
The result of the Argumentation Coefficient (Ka) should sum the degree of influence of each expert (high/medium/low).
Table 2 Calculation of Ka for K for each expert
| Source of argumentation | Degree of influence A | Degree of influence M | Degree of influence B |
|---|---|---|---|
| Research conducted by the expert | 0.3 | 0.2 | 0.1 |
| Professional experience in the field of analysis | 0.5 | 0.4 | 0.2 |
| Technical work experience – non-theoretical | 0.05 | 0.05 | 0.05 |
| Personal knowledge on the subject | 0.05 | 0.05 | 0.05 |
| Personal knowledge on the subject outside the expert's country of origin | 0.05 | 0.05 | 0.05 |
| Expert intuition | 0.05 | 0.05 | 0.05 |
Source: Created by the authors based on Cabero-Almenara and Infante-Moro (2014).
Considering the Ka value of each expert, we calculated the K to determine the value of the panel for this study.
As shown in Table 3, we did not exclude any participants’ responses from either questionnaire, as the expert competence coefficients were optimal (K≥0.8).
Table 3 Calculation of the Expert Competence Coefficient (K)
| Expert Competence Coefficient (K) | Expert | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
| Assessment of the degree of knowledge coefficient (Kc) | Kc x 0.1 | |||||||||||
| Not a specialist and possesses no knowledge of the subject (0) | ||||||||||||
| Not a specialist but possesses limited knowledge of the subject (3) | X | |||||||||||
| Not a specialist but possesses knowledge of the subject (6) | X | X | ||||||||||
| Specialist and possesses considerable knowledge of the subject (9) | X | X | X | X | X | X | ||||||
| Specialist and possesses comprehensive knowledge of the subject (10) | X | X | X | |||||||||
| Pre-calculated value of Ka | 0.8 | 0.8 | 0.8 | 1 | 0.7 | 0.6 | 0.5 | 0.8 | 1 | 0.8 | 1 | 0.8 |
| Expert Competence Coefficient (K) | 1.4 | 1.8 | 1.8 | 1.9 | 1 | 1.5 | 1.1 | 1.7 | 1.9 | 1.7 | 1.9 | 1.8 |
Source: Created by the authors based on Cabero-Almenara and Infante Moro (2014).
Results
The findings were structured and grouped by approach: (a) the consumption patterns of generation Alpha from an audio-visual and advertising perspective and (b) the potential effects of such content on children from an expert psychological perspective.
The consumption of generation Alpha on TikTok
Based on the first audio-visual and advertising approach, the results were organized according to the following objectives: (O1) analysis of audio-visual consumption, (O2) relationship between the gender of children and TikTok consumption, and (O3) identification of advertising content on TikTok.
O1: Audio-visual analysis of content targeted at children
First, we conducted an analysis to explore the correlations between audio-visual variables (shots, graphics, and effects used) and the independent variable “time” on TikTok videos featured in the “For You Page” for young users. The Kolmogorov-Smirnov test indicated that all variables deviated significantly from a normal distribution. Specifically, for the “shot” variable, K-S (500)=0.229, p<0.001; for “graphics”, K-S(500)=0.485, p<0.001; for “time”, K-S(500)=0.191, p<0.001; and for “effects”, K-S(500)=0.491, p<0.001. Consequently, we employed the Spearman test to identify significant correlations among the non-parametric data (Table 4).
Table 4 Gender and content Spearman correlations
| Shot | Graphics | Effects | |
|---|---|---|---|
| Time | .299** | .029 | .230** |
| Sig. | .001 | .512 | .001 |
| p | .54 | .17 | .47 |
| 1-β | 1 | .99 | 1 |
**The correlation is significant at the 0.01 level.
The test revealed significant correlations between “shot” and “time” (r=0.299, p<0.001) and between “effects” and “time” (r=0.230, p<0.001). However, no significant correlation was found between “graphics” and “time” (r=0.029, p=0.512). These coefficients indicated moderate effect sizes for the relationships between shot and time (r=0.299) and between effects and time (r=0.230), suggesting that variations in shot types and the use of effects are moderately associated with changes in video duration. The non-significant correlation between graphics and time (r=0.029) implied that graphics play a less pivotal role in determining video length in the youngest consumption of TikTok.
To further understand the association between shot and time, we performed a chi-square test and calculated the Cramer’s V. The chi-square test revealed a significant association between both variables: X²(N=500)=268.152, p<.001, Cramer’s V=.221. This showed a moderate relationship between the type of shot and the duration of the TikTok videos.
We observed that certain types of shots were particularly prevalent for specific durations. For instance, “medium shots” were the most frequent across various time segments, including 5-10 seconds (n=20), 11-15 seconds (n=25), and 41-50 seconds (n=7). In contrast, “extreme closeup shots” were rare, appearing predominantly in the 31-40 seconds (n=2) and 51-60 seconds (n=1) categories. “Multiple shots” were significantly more common in longer videos, with notable counts in the 1-minute (n=29) and 2-minute (n=26) categories.
The preference for “medium” and “multiple shots” in specific time segments reflects a strategic approach by content creators and brands to maintain the youth viewer attention. Particularly, “medium shots” provide a balanced view that can capture both action and context, making them versatile for various types of content. The frequent use of “multiple shots” in longer videos revealed an effort to keep the content dynamic and interesting, which is crucial for retaining user attention over extended periods on an ephemeral-content platform.
We also analyzed the association between the effects and time using the chi-square test and Cramer’s V. The chi-square test results showed a significant association, X²(N=500)=73.820, p<.001, Cramer’s V=0.272. An exploration of the cross-tabulation between these variables revealed that videos with effects were notably more prevalent for shorter durations, specifically in the 5-10 seconds (n=37) and 11-15 seconds (n=28) categories. Conversely, videos without effects were more evenly distributed across various time segments, with a substantial presence for longer durations, such as 51-60 seconds (n=45) and over 1 minute (n=54).
The expected counts provided further insight into these patterns. For videos with effects in the 5-10 seconds category, the observed count (n=37) significantly exceeded the expected count (17.8), whereas the observed count for videos without effects in the same category (n=55) was lower than the expected count (74). This finding implies a strong preference for using the effects of shorter videos.
On the other hand, for posts over 1 minute in length, the observed count for videos with effects (n=10) was lower than the expected count (12.4), indicating a lesser tendency to use effects in longer videos. This trend is further supported by the linear-by-linear association (22.906, p<.001), reinforcing the notion that the use of effects is strategically employed based on video length. Thus, the inclination for effects in shorter videos highlights a critical strategy for content creation in TikTok. These effects may quickly capture and retain the attention of children, which is essential for short-form video content.
O2: Relationship between children’s gender and TikTok consumption
Subsequently, we applied the Kolmogorov-Smirnov test to assess the normality of the distribution among variables related to gender and content characteristics, including content type (themes), level of communicative formality, performer, and the nature of the content. Our analysis included 500 videos with a standardized sample size of n>50. The results indicated that the significance level was below p>.05 for all variables (K-S(500)=.361gender; .166type of content; .380level of communicative formality; .285performer; .453nature of content, p=.001). Based on these findings, we proceeded with the Spearman’s correlation test for non-parametric data (Table 5).
Table 5 Gender and content Spearman correlations
| Gender | Type of content | Level of communicative formality | Performer | Nature of content |
|---|---|---|---|---|
| -.106* | .031 | .003 | -.110* | |
| Sig. | .017 | .493 | .939 | .014 |
| p | .32 | .17 | .05 | .33 |
| 1-β | .99 | .99 | .97 | .99 |
*The correlation is significant at the 0.05 level.
We found that gender did not appear to affect the type of content offered to children in the “For You Page” section of TikTok. In this case, significant relationships between gender and “type of content” and “nature of content” stood out, with negative relationships, medium effect sizes, and a high probability of being real effects due to their high statistical power. To deepen our understanding of these relationships, we employed the chi-square test and Cramer’s V test.
Our analysis of the association between gender and “type of content” (X 2(N=500)=113.779; p<.001, Cramer’s V=.477) revealed a highly significant and moderately strong correlation. Males demonstrated a marked preference for content related to “politics” and “sports”, whereas females showed a predilection for “fashion and beauty” as well as “lifestyle”. This gender-based divergence in content engagement suggests that underlying sociocultural factors influence content consumption patterns.
Furthermore, our analysis of the relationship between gender and the “nature of the content” exposed a significant yet comparatively weaker association (X 2(N=500)=18.844; p<.001, Cramer’s V=.194). This result indicates that although gender influences content consumption, its strength varies. Delving into the data, we found that a young boy profile receives more content related to “influencer-driven advertising” (nine instances) than girls (three instances). Conversely, girls consumed substantially higher engagement with “original non-promotional content”, recording 221 instances versus 157 instances for males. This indicates a stronger broadcast of authentic and creative content among girls. Both genders show nearly identical consumption of “viral content” that mimics trends, with boys at 20 instances and girls at 21 instances. This suggests a universal appeal for trending content, reflecting similar trendfollowing behaviors regardless of gender.
However, a notable gender difference emerged in consumption with “business advertising content”, where boys (43 instances) were more than twice as engaged as girls (21 instances). This indicates that boys may be more targeted by direct commercial messages. Additionally, media channels remained low for both genders, with two instances for boys and three for girls, suggesting a reduced broadcast of traditional media videos among young TikTok users.
These findings highlight the pivotal role of content type and nature in shaping gender-specific engagement in TikTok in the generation Alpha. Despite diverse factors such as video performers, communicative style, or technological affordances, the type and nature of content remain the most salient factors in understanding gender dynamics on this platform.
O3: Advertising content targeted at children on TikTok
Finally, we observed that the brands most frequently appearing in the content viewed by the children on TikTok were predominantly related to clothing, fashion, accessories, audio-visual consumption, and technological tools. Brands such as Shein, AliExpress, and Vinted were most advertised in the fashion and fast fashion sectors (Table 6).
Table 6 Brands with the greatest presence on TikTok for the 14-year-old profiles
| Brand | Sector |
|---|---|
| Shein | Fast fashion retailers. |
| La Cuponera | Online loyalty programs to offer branded product deals. |
| Disney + | Video on-demand streaming media platforms. |
| AliExpress | Online retailers. |
| Vinted | Fast fashion retailers. |
| Al Cleaner | Free Android apps. |
Source: Created by the authors.
It is essential to highlight that, from the analyzed content, advertisements constituted 13.2% of the total, ranking third among the categories with the highest presence; following humorous content (25.2%) and dance content (16.2%). Furthermore, regarding promotional content, we identified the following strategies:
Original content with no promotion intent (75.6%).
Direct promotional content from commercial enterprises (12.8%).
Viral content emulating trends and challenges featuring brands (8.2%).
Influencer-driven advertising (2.4%).
Cross-media content (1%).
Qualitative notes were gathered on the content viewed during analysis. In this sense, in several videos classified as “original content with no promotional intent” or “viral content that emulates trends and challenges”, brands appeared intentionally, reminiscent of the product placement advertising practice. Additionally, in some of these videos, the interlocutors used aggressive language, pushing the user toward the purchase or use of the product.
O4: Effects of promotional and fragmented consumption on generation Alpha
To address the fourth objective concerning the impact of the analyzed content on TikTok, the findings were shared with experts. First, it is important to highlight that 77% of psychologists determined that social media, in general, negatively affects the cognitive and social development of children. Furthermore, 83% held negative opinions about TikTok.
In this context, we divide the results into three sections: (a) audio-visual effects, (b) advertising effects, and (c) expert recommendations to protect future generations in their audio-visual and advertising-driven consumption of TikTok.
TikTok audio-visual effects
Experts unanimously indicated that the continuous consumption of short videos (ranging from 10 to 15 seconds) composed of multiple shots negatively impacts young people. They highlighted that this type of daily, sustained consumption diminishes attention spans in adults, but for young people, it significantly impairs their ability to concentrate on any task or activity outside social media. They also noted that this pattern of audio-visual consumption could erode their patience and tolerance levels.
Notably, 32.6% of the analyzed videos were between 5 and 15 seconds long and featured multiple shots. Experts explained that children’s brains adapt to these fragmented stimuli, leading to heightened addiction and the development of compulsive behaviors that increase the need for immediacy (in consumption, acquisition, communication, and other areas) in their daily lives.
From a media consumption perspective, psychologists pointed out that the design of this platform prioritizes emotional, relational, and narrative elements in order to capture young people’s attention. As a result, TikTok generates cerebral hyperstimulation, which diminishes attention and motivation for other informational formats or activities requiring sustained attention, such as studying or engaging in family conversations.
TikTok advertising effects
As previously noted, 13.2% of the examined content comprised advertisements or content related to brands, products, or services. Given these data, psychologists indicated that generation Alpha members lack the tools and critical perspective to responsibly identify and evaluate advertising content, making them vulnerable individuals. They particularly emphasized the issue of masked or non-explicit advertising by opinion leaders, such as influencers, which leads to misconceptions about the veracity of content or products.
88% of the experts also pointed out that any uncontrolled advertising content on TikTok is indeed harmful to younger generations, as it creates needs from an early age that hinders healthy cognitive development. Simultaneously, they noted that this type of advertising (unregulated, influencer-driven, subliminal, and so on) fosters more consumerist behaviors, which can lead to anxiety, since young people do not have the financial resources to acquire certain products or services. They also highlighted that these strategies could affect their capacity for self-control in future adult consumption.
When discussing the types of advertising content (fashion, accessories, lifestyle, tech applications, and others) and identified gender bias (more advertising in the male profile than in the female profile), the 82% of the experts believed that it negatively or very negatively affects young people. They highlighted that excessive advertising related to lifestyle or fast fashion products contributes to unrealistic comparisons with beauty standards, resulting in low self-esteem and personal insecurity. Some experts additionally stated that brands target these vulnerable audiences, circumventing current regulations on TikTok.
Furthermore, when evaluating why more advertising might appear directed at boys’ profiles than girls’ profiles, the experts agreed. If this phenomenon is driven by TikTok’s algorithmic recommendation system, brands will reinforce gender gaps in the consumption of advertising content targeted at children.
Expert consensus: a multifaceted regulation of TikTok to protect children
Of the experts, 72.7% asserted that generation Alpha children should not have access to their smartphones. Furthermore, 82% believed that access to TikTok and similar social media platforms should be not permitted. Although they acknowledged that integrating technology into young people’s lives is inevitable and partly essential, they called for a stronger and more effective parental supervision system to prevent children from engaging in continuous and uncontrolled advertising on the platform.
Psychologists have also highlighted the negligent use of the internet by many global users, which has inevitably affected children through the design of these platforms. They emphasized that children must be protected from any factors that could harm their physical development and mental health, identifying TikTok as one of the most detrimental apps for this group due to its fragmented and fleeting audio-visual content and uncontrolled or subliminal advertising.
To address this issue, 45.4% of the psychologists recommended an outright ban on creating social media profiles for children. Additionally, 36.6% advocated the implementation of more thorough parental controls than currently available on TikTok. Only 19% of the participants deemed it essential to enforce laws regulating these social media platforms and their content. They explained that maintaining effective parental control is challenging because of the existing technological generational gap, advocating for shared responsibility among parents, guardians, app developers, and governments to protect children from harmful content.
Discussion and conclusions
Alpha members currently represent the most vulnerable demographic for advertising on social media platforms (Carnelian-Tantra, 2022; Martínez-Estrella et al., 2023; Popa et al., 2023), particularly on TikTok. This study presents several findings that indicate the potential effects of consuming audio-visual and promotional content in this demographic group. We found that the hyperconnectivity fostered by this system, as noted by Danilova (2022), impacts young people’s mental health by accelerating fragmented and advertisement-laden consumption, leading to the following conclusions:
C.1. Videos appearing during TikTok consumption on youth profiles feature short formats with multiple shots, potentially impairing activities requiring sustained attention (such as studying, physical activities, and others) and fostering anxious behaviors (Zheluk et al., 2022). Additional studies have confirmed that highly fragmented and visually stimulating content can reduce young people’s concentration ability and increase anxiety levels (Abidin, 2021; Montag and Markett, 2024). Similar to video games or streaming platforms, it would be beneficial to include visual or auditory warnings on videos that might be harmful to young viewers or those with photosensitivity to TikTok.
C.2. TikTok’s content segmentation varied according to the user’s gender. Boys encounter more advertising content (70%) than girls do (30%). Additionally, boys tend to consume more political or sports content, whereas girls are more exposed to beauty, makeup, and lifestyle content. Further research supports that such segmentation can lead to greater exposure to specific types of advertising based on gender, reinforcing biases, and perpetuating inequalities in young’s people perceptions and aspirations (Ionescu and Licu, 2023). This content can perpetuate the uncontrolled dissemination of advertising, introducing gender biases in the consumption patterns of future generations (Turuna et al., 2024).
C.3. Advertising ranked third among the content consumed by young people on TikTok. Over 10% of this category is described as subliminal or influencer-driven advertising (Zozaya-Durazo et al., 2022), with no clear indication of the promotional nature or purpose of the video. The identified advertising mainly promotes fast fashion and lifestyle brands. Additional research underscores the need for stricter regulation and transparency measures in digital platform advertising to protect young people’s mental health (García-Marín and Salvat-Martinrey, 2022; Bueno-Fernades and Campos-Pellanda, 2022). Such messages can negatively impact young people by distorting the concept of
a “perfect” body image (Harriger et al., 2023), increasing objectification, and causing mental disorders related to individual and collective body image.
C.4. Experts collaborating on this research, recognizing the potential effects of such applications, advocate for a multifaceted intervention to mitigate TikTok’s impact on the Alpha generation. Issues range from addictive and uncontrolled consumption (Miao et al., 2023) to an increasingly misinformed society (Alonso-López et al., 2021) and rising mental health problems (Zheluk et al., 2022). It is crucial to emphasize and implement media and information literacy for new generations, enhance shared parental control systems to bridge the generational gap, and promote governmental intervention involving competent bodies in the design and regulation of this application (Montag et al., 2021; McCashin and Murphy, 2022; Miao et al., 2023). Historically applied to other mass media, it is imperative to protect and safeguard young people against challenges emerging from inherently commercial fields on platforms built on ephemeral, algorithmic, opaque, and audio-visual foundations.
Limitations and future research lines
One of the limitations of the present study involves the analysis of consumption from profiles created ad hoc to explore youth engagement on TikTok. The interaction and intervention of researchers may have biased the results because of the platform’s algorithmic recommendation system. Consequently, we did not capture the opinions and experiences of primary users, namely young people, as this was an exploratory and preliminary analysis. In this sense, it would be valuable to comprehend the perspectives of generation Alpha regarding the types of audio-visual and advertising content they engage in and consume on TikTok.
Moreover, during the analysis of quantitative data, we identified advertisements of questionable ethical quality (considering that the profiles were expressly “navigated by children”), which precluded a more in-depth and qualitative exploration. From this perspective, it is essential to examine how fragmented-brand advertising strategies are evolving on social media as popular as TikTok, which appears to circumvent regulations and restrictive moderation systems designed to protect children.
