Next Article in Journal
The Shaping of Contemporary Morality in Intimacy Decision-Making in Britain
Next Article in Special Issue
Emotional Intelligence, Immediate Auditory Memory, and ICT in Primary Education: A Neuroeducational Approach
Previous Article in Journal
School-Based Health Services to Improve Youth Access to Reproductive Health Care
Previous Article in Special Issue
Who Teaches Older Adults? Pedagogical and Digital Competence of Facilitators in Mexico and Spain
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Social Sciences
Volume 15
Issue 1
10.3390/socsci15010049
socsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Levels of Academic Engagement and Social Media Addiction Among University Students: A Comparative Study

by
Yosbanys Roque Herrera
1,*,
Santiago Alonso García
2,
Dennys Vladimir Tenelanda López
3 and
Juan Antonio López Núñez
2
1
Facultad de Ciencias, Escuela Superior Politécnica de Chimborazo, Riobamba EC060155, Ecuador
2
Departamento de Organización Escolar y Currículo, Universidad de Granada, 18071 Granada, Spain
3
Facultad de Ciencias de la Salud, Escuela Superior Politécnica de Chimborazo, Universidad Nacional de Chimborazo, Riobamba EC060155, Ecuador
*
Author to whom correspondence should be addressed.
Soc. Sci. 2026, 15(1), 49; https://doi.org/10.3390/socsci15010049
Submission received: 29 October 2025 / Revised: 12 January 2026 / Accepted: 15 January 2026 / Published: 20 January 2026
(This article belongs to the Special Issue Educational Technology for a Multimodal Society)
Versions Notes

Abstract

Social media is a valuable resource in many spheres of life in the 21st century; however, excessive, uncontrolled use is associated with various adverse health conditions. In this study, we used a quantitative approach, an observational design, and a comparative scope to compare levels of academic commitment and social media addiction, and their respective dimensions, grouping participants according to various sociodemographic and educational criteria. A total of participants was 1200 students (65.3% female) with an average age of 21.4 years, from the Faculty of Health Sciences at the National University of Chimborazo, Ecuador, and data were collected using the Ultrecht Academic Commitment Scale and Social Media Addiction Questionnaire. When grouped by major, statistically significant differences were found only for dedication (p = 0.038), lack of control over social media use (p = 0.016), and excessive social media use (p = 0.002). When grouped by social media use, there were statistically significant differences in all the dependent variables, with p-values ranging from 0.000 to 0.011. Regarding the frequency of social media use, no significant differences were found in academic engagement (p ≥ 0.05), while the opposite was observed for social media use. A comparative analysis identified categories with significant differences. The results enabling an accurate diagnosis and the adoption of the most appropriate educational strategies; also serves as a theoretical and methodological basis for further research on the subject.

1. Introduction

1.1. Social Media Addiction

Contemporary society has built entire social, economic, political, cultural, and educational, and other structures around the Internet, and the diversity of the current and potential uses of this resource is overwhelming. In 2020, an estimated 4.54 billion users worldwide used Internet services frequently, a figure that rose to 4.9 billion in 2021. Social media is one of the most popular resources due to its versatility and ease of use, and it is estimated that there were 4.62 billion active users in 2022, with an average connection time of 2 h and 27 min (Condori-Sinty et al. 2023; Gallego-Arrufat and Torres-Hernández 2025; Pellegrino et al. 2022; Salas-Blas et al. 2022).
Social media is a valuable resource in many areas of life in the 21st century, offering multiple advantages through its ability to allow people to interact with others. However, its excessive and uncontrolled use has been associated with various adverse health consequences, such as suicidal tendencies, loneliness, anxiety, and eating disorders, among others, in addition to other risks linked to the misuse of technology related to sexting, cyberbullying, privacy violations, identity theft, and others. Therefore, an addiction to social media can affect the academic performance, social behavior, and interpersonal relationships of students (Kelly et al. 2018; Pellegrino et al. 2022; Marinoni et al. 2024).
Lee et al. (2023) and Vera-Muñoz et al. (2024) significantly linked social media addiction with stress, anxiety, and depression in a population of university students. Likewise, Suárez-Perdomo et al. (2023) noted that students with this problem spend excessive amounts of time online, which leads to procrastination in their academic activities and a decline in their academic performance. These last authors recommend developing educational actions to raise students’ awareness of appropriate social media use, to prepare teachers to use it in teaching, and to regulate its use by students during teaching activities.
Based on Maslow’s hierarchy of needs, Chen et al. (2022) identify social needs and argue that individuals require a sense of belonging through interpersonal communication. Social media facilitates this process by offering the safety of distance, anonymity, and the ability to disconnect at any time. Thus, this Internet resource provides a sense of social connection primarily to young people and adolescents. These authors argue that the effective use of social media facilitates access to information, fosters positive emotions, motivation, and self-esteem, and can even inspire individuals to lead processes and/or movements.
However, social media addiction entails a set of potential risks for younger users, primarily antisocial behavior and exposure to inappropriate content. Several authors recommend the reinforcement of actions that promote the appropriate use of these networks in the academic environment through coordinated, active parental mediation. In this regard, some of the elements that should be controlled include the time spent on social networks, the frequency of social media connection, the reasons for using social media, and perceptions of the reasons for controlling social media use, among others (Al-Samarraie et al. 2022).

1.2. Academic Engagement

Academic engagement is understood as the set of intentional, proactive, and constructive acts that students develop during their teaching–learning process (Reeve and Shin 2020; Rigo et al. 2021). Other authors agree that it is a multifactorial construct that includes the dedication and effort that students give to improve their learning outcomes and achieve their goals, overcoming the challenges that arise during the process in a motivated way, which is marked by emotional ties to their academic training and institution (Albornoz et al. 2021; Tacca-Huamán et al. 2021; Wang et al. 2021).
Academic engagement requires university students to be satisfied with their professional training and the environment in which it is delivered, which is reflected in the emotional and cognitive dimensions. Thus, the way that students perceive institutional prestige, the training of the teaching staff, and the quality of the facilities and processes become key elements (de-Besa-Gutiérrez et al. 2024; Froment and de-Besa-Gutiérrez 2022).
The results of several studies on academic or school engagement (as some authors also refer to it) in adolescents and young people have shown that it is associated with social relationships with peers, teachers, and close family members and the achievement of effective emotional ties; however, for the most part, no link has been identified between the sociodemographic variables of sex and age (Ramos-Vera et al. 2023).
Fuster-Guillen and Baños-Chaparro (2021) applied Bayesian statistics and found no significant differences in academic engagement among Peruvian university students grouped by sex and age; however, Sadoughi and Hejazi (2021) observed statistically significant differences between sexes among Iranian students. Considering these results and those of other research, it can be inferred that no regularity is observed in this demographic variable regarding academic engagement.
In higher education, the commitment of students to their professional training entails pursuing high academic performance and making a significant contribution to society. It is a fact that this phenomenon directly impacts educational progress and retention, requiring a high level of involvement in the teaching–learning process across a wide range of tasks and activities (Aspée et al. 2021; Perkmann et al. 2021).
Escofet-Roig et al. (2021) designed a strategic methodology for developing academic engagement based on co-design, applying a participatory construction process that involves the university student as a change implementer, with five fundamental principles: respect, reciprocity, responsibility, reflection, and review.
Another construct used to conceptualize academic commitment considers four other dimensions (Lara et al. 2022; Lira-Munizaga 2024; Morcillo-Martínez et al. 2021; Axelrod and Santagata 2022):
  • The behavioral dimension, which is expressed through attitudes that guarantee adequate production and participation in curricular and extracurricular activities.
  • The emotional dimension, which is expressed through positive affective manifestations related to learning (enjoyment, appreciation of the task, etc.).
  • The cognitive dimension, which includes reflection, the use of effective learning strategies, and the search for an understanding of complex ideas.
  • The social dimension, which refers to the quality of the way that students interact with their peers inside and outside the school environment.
Haseli-Songhori and Salamti (2024) conducted their research with the participation of 677 undergraduate students from Farhangian University of Kerman, applying a structural equation model that showed the mediation of psychological capital in the relationship between academic support and academic engagement (β = 0.58, p < 0.01); in addition, educational support (β = 0.69, p < 0.01) and psychological capital (β = 0.39, p < 0.01) were found to be predictors of academic engagement.
Zhu et al. (2021) note that parental support and the way that parents approach their children’s education are factors that influence their children’s academic engagement. These researchers found a significant correlation between perceived parental support and dedication to academic tasks (r = 0.23; p < 0.01).
Given the potential complications that psychological problems can cause for students, Wang et al. (2023) investigated academic engagement among 17,341 high school students from 17 provinces in China and found an inverse correlation between academic engagement and anxiety (p = 0.01; r = 0.54).
In addition to the aforementioned background, the following studies can be mentioned:
In a population of university students, Roque-Herrera et al. (2025) applied a linear regression model and found that the level of addiction to social networks significantly explained the level of academic engagement (R2 = 0.112, p < 0.001).
Brailovskaia and Margraf (2024) conducted a study involving 9418 participants from nine countries and found a statistical correlation (p < 0.001) between moderate intensity of social media addiction and daily time spent on social media. Similarly, Huang et al. (2023) significantly correlated internet connection time with social media addiction in 598 Taiwanese university students (r = 0.29, p < 0.01).
In another study, Valencia-Ortiz et al. (2021) found that the number and type of social media platforms used by Mexican students participating in their research had a moderate statistical effect (p < 0.01) on increased addiction to these platforms. Similarly, Ramírez-Gil et al. (2021) linked problems related to social media use with the way these platforms were used and an obsession with staying informed among Mexican university students.

1.3. Current Study

The researchers started with the following scientific question: Are there significant differences in the levels of academic engagement and social media addiction between groups of students according to various sociodemographic and academic criteria in a health sciences program setting?
Given the importance that the scientific community places on studying the phenomena under investigation, we conducted a study to compare levels of academic engagement and social media addiction, along with their respective dimensions, grouping participants based on various sociodemographic and academic criteria in a health sciences program setting at an Ecuadorian university.
Thus, the following research hypothesis was proposed: There are statistically significant differences between the levels of academic engagement and social media addiction of the participants between groups of students according to various sociodemographic and academic criteria.

2. Materials and Methods

Using a quantitative approach, an observational, non-experimental, comparative, cross-sectional design was employed in this research.

2.1. Participants

All members of the population were included in this study, which consisted of 1200 students from the Faculty of Health Sciences at the National University of Chimborazo, Ecuador. The students were aged 18 to 27 years and were enrolled in semesters 1–6 in the first academic term of 2023 (Table 1). The 65.3% was female and the average age was 21.4 years.

2.2. Tools

The following instruments were used in this study: the Ultrecht Academic Engagement Scale (UWES-S-17) and the Social Media Addiction Questionnaire (SMAQ).
The UWES-S-17 (Cruzat-Aliaga 2020) is made up of 17 items, which are ranked according to a seven-value, Likert-type scale: 0—not at all; 1—almost not at all; 2—rarely; 3—sometimes; 4—quite a bit; 5—frequently; 6—always. These items are used to establish the state of academic commitment and its three dimensions, which are as follows:
  • Vigor (items: 1, 4, 8, 12, 15, and 17): Vigor is determined by persistence, will, energy, and mental resistance to challenges arising from efforts inherent in academic work, which involves facing various difficulties related to the environment and task.
  • Dedication (items 2, 5, 7, 10, and 13): A student’s dedication is relative to the intensity of their involvement in their academic self-preparation, giving it meaning, significance, and enthusiasm, finding inspiration and taking pride in their work, and overcoming challenges.
  • Absorption (items: 3, 6, 9, 11, 14, and 16): Absorption refers to the intensity with which the student concentrates on their academic self-training, according to the magnitude of their focus on completing the task.
Tristán-Monrroy et al. (2021) validated the UWES-S-17 in a study conducted at the Autonomous University of San Luis Potosí, which involved 223 students. The authors reported an explained variance of 66.82% and an adequate model fit, with an RMSEA (root-mean-squared error of approximation) of 0.048 and a CFI (comparative fit index) of 0.990. Likewise, Guerra-Díaz and Jorquera Gutiérrez (2021) determined that the three dimensions show adequate reliability values: Vigor (McDonald’s ω = 0.791); Dedication (McDonald’s ω = 0.829) and Absorption (McDonald’s ω = 0.709).
The SMAQ (Escurra-Mayaute and Salas-Blas 2014) is structured into two sections: a general section that addresses the variables of career, social networks used, frequency of social network connection, uses of social networks, and reasons for self-controlling social network use; and a second section that includes 24 items that make it possible to measure the level of social network addiction and its three dimensions through a Likert-type scale with five possible values: 0—never; 1—rarely; 2—sometimes; 3—almost always; and 4—always. The three dimensions of social network addiction are as follows:
  • Obsession with social networks (items 2, 3, 5, 6, 7, 13, 15, 19, 22, and 23), which is characterized by the intensity of the individual’s impulse to connect to the Internet, which can generate anxiety.
  • Lack of personal control (items 4, 11, 12, 14, 20, and 24), which is related to the inability to self-regulate compulsive behavior by connecting to social networks.
  • Excessive social media use (items 1, 8, 9, 10, 16, 17, 18, and 21), which can be measured, especially when it exceeds personal needs.
In validating the SMAQ, Rosero-Bolaños et al. (2022) reported favorable Aiken’s V values across all criteria: clarity (0.92), coherence (0.97), and relevance (0.99). The authors also determined Cronbach’s alpha values ranging from 0.82 to 0.93 across its dimensions and 0.95 globally. The results of other tests conducted by these authors allowed for the quantitative corroboration of the above: TLI (Tucker–Lewis index) = 0.929; RMSEA = 0.054; and CFI = 0.936.

2.3. Procedure

The authors conducted this study in compliance with the ethical principles of scientific research: autonomy, beneficence, and nonmaleficence. Participants provided informed consent, and the institutional authorities also granted permission to administer the instruments. Data were organized using SPSS software version 18.0 (IBM, headquartered in New York, NY, USA), and the results were used solely for scientific and academic purposes.

2.4. Statistical Analysis

The data were organized and processed using SPSS version 18.0 statistical software (IBM, headquartered in New York, NY, USA), employing the statistical tests described below. During the data collection and processing, objectivity was sought in the participants’ responses, which reduced the likelihood of bias. Additionally, no missing data was observed.
The study variables were characterized using descriptive statistics, including relative frequency analysis, as well as the Pearson χ2 test to assess the association between the main variables and their dimensions.
One-way ANOVA inferential statistical tests (Parra-Tijaro et al. 2022), Tukey–Kramer multiple comparisons (Montoya-Reyes et al. 2024), and Tukey’s HSD (Saucedo-Uriarte et al. 2025) allowed for a comparison of the levels of social media addiction, academic commitment, and their respective dimensions, grouping the population based on their careers, the social networks they used, the frequency of their social network connection, and their reasons for self-controlling their social media use.

3. Results

The population was dominated by students with an academic commitment level classified as sufficient (95.8%); in addition, the average level was present in most participants in terms of global social network addiction (91.0%) and its dimensions, the values of which ranged between 51.4% and 54.6%, except for the values for excessive social network use, among which the high level stood out (60.2%). Both main variables were significantly associated (Pearson χ2, p < 0.05).
The analysis of the level of academic engagement revealed that only 4.2% of participants were below the average category, which predominated (40.5%). The majority of students showed a medium level of overall social media addiction (93.7%) and in the respective dimensions (between 52.4% and 55.7%). The situation was different for excessive social media use, with 63.5% at the high level.
The level of academic commitment and its corresponding dimensions (Table 2) (vigor, dedication, and absorption) were compared by grouping the students in the population by career, with statistically significant differences only in the case of dedication (p = 0.038) and an F value greater than one (2.364).
The Tukey–Kramer multiple comparisons test for the programs, based on the level of dedication, revealed a statistically significant difference between Physical Therapy and Clinical Laboratory Science (p = 0.041). Furthermore, processing the subsets using Tukey’s HSD test showed that the former had the lowest mean value (3.764), while the latter had the highest (4.060).
The intergroup comparison by career, relative to the level of social media addiction and its respective dimensions (Table 2) (obsession, lack of control in its use, and excessive use), showed statistically significant differences in terms of lack of control in social network use (p = 0.016, F = 2.792) and excessive social network use (p = 0.002, F = 3.926).
The analysis of the level of excessive social network use through the Tukey–Kramer multiple comparisons test identified statistically significant differences between some schools: Clinical Laboratory with respect to Clinical Psychology (0.013), Medicine (0.010), and Dentistry (0.004), as well as between Nursing and Clinical Psychology (0.013) and between Medicine and Nursing (0.010). The subset analysis using the Tukey HSD test showed the lowest mean in Clinical Laboratory (2.480) and the highest in Dentistry (2.689).
Multiple comparisons of the level of lack of control over social media use using the Tukey–Kramer test showed statistically significant differences in the Clinical Laboratory program compared to Clinical Psychology (0.046) and Dentistry (0.009), as well as between Nursing and Clinical Psychology (0.0146). Subsets were compared using the Tukey HSD test; the lowest mean value was observed in the Clinical Laboratory program (2.2850) and the highest in Dentistry (2.4756).
The level of academic commitment and its corresponding dimensions were compared (Table 3) by grouping the population based on the social networks they used, which allowed us to identify statistically significant differences in all the dependent variables, with p-values ranging from 0.000 to 0.011; in all cases, statistically significant differences were found in the use of Twitter plus Facebook and/or WhatsApp with respect to Instagram plus Facebook and/or WhatsApp (p < 0.05), according to the Tukey–Kramer multiple comparisons test.
When comparing the groups established based on the social networks they regularly used (Table 3), paying attention to the levels of social media addiction and the corresponding dimensions, significant differences were found in the variables obsession (p = 0.028, F = 3.030), lack of control over social network use (p = 0.004, F = 4.486), and excessive social network use (p = 0.001, F = 5.468).
Considering these three variables as dependent variables, statistically significant differences were observed in all of them for the exclusive use of Facebook and/or WhatsApp compared to Twitter plus Facebook and/or WhatsApp (p < 0.05), as determined by the Tukey–Kramer multiple comparisons test.
Grouping participants according to the frequency with which they connected to social networks, the comparative analysis of data on academic commitment and its dimensions (Table 4) revealed no statistically significant differences (p ≥ 0.05).
When comparing the level of social media addiction and its corresponding dimensions (Table 4), grouping students in the population based on their frequency of social media connection, statistically significant differences (p = 0.000) were established in all dimensions of social media addiction; however, this characteristic was not observed at the overall level of this variable (p = 0.121).
The analysis of the dimensions of the level of social media addiction using the Tukey–Kramer multiple comparisons test allowed us to identify statistically significant differences in the frequency of social media connection a few times a week compared to almost all day (p < 0.05) in all of the dimensions, the average values of which were the lowest in the first category (between 2.3053 and 2.2421) and the highest in the second (between 2.5561 and 2.6061). 2.7349, according to the Tukey HSD test.
The comparison of the academic commitment levels and their corresponding dimensions according to the students’ social network use (Table 5) revealed statistically significant differences across all the dependent variables (p = 0.000).
Tukey’s HSD test was used to compare subsets of these variables, created from the population’s social network use, and the greatest differences in the means were found between the entertainment category (between 3.3839 and 3.8150) and the exchange of academic information (between 3.8468 and 4.2523).
The grouping of the students in the population based on their social network use, their level of social network addiction, and the corresponding dimensions were compared (Table 5), which allowed us to identify statistically significant differences in the global (p = 0.011) and obsession (p = 0.014) levels of this variable.
When considering the level of social network addiction in the population, the Tukey–Kramer multiple comparisons test allowed us to identify statistically significant differences in the students’ social network use: marketing of products related to entertainment (0.023) and exchange of academic information (p = 0.037).
The groups established based on causes for self-regulating social network use were compared according to the levels of academic commitment and its dimensions (Table 6), revealing statistically significant differences in the variables vigor (p = 0.008) and dedication (p = 0.015).
The analysis of the level of vigor through individual means, using the Tukey–Kramer multiple comparisons test, made it possible to establish statistically significant differences between the reasons for self-controlling social network use: “I see no reason to avoid using social networks” and “the possibility of being victims of crimes or harassment” (p = 0.002).
Comparative processing of the vigor-level subsets using Tukey’s HSD test indicated that the lowest mean value on the scale was “I see no reason to avoid using social networks” (3.196), and the highest mean value on the scale was the “possibility of being victims of crimes or harassment” (3.582).
The level of social network addiction and its corresponding dimensions were compared by grouping students based on the causes for their self-control over their social network use (Table 6), revealing statistically significant differences only in the level of obsession (p = 0.005).
Regarding the level of social network obsession in the population, the Tukey–Kramer multiple comparisons test showed a statistically significant difference between the categories “I do not see reasons to avoid the use of social networks” and “the possibility of being victims of crimes or harassment” (p = 0.012).
The comparison of the subsets of the level of social media obsession using Tukey’s HSD test showed the lowest mean value in the category “the possibility of being victims of crime” (2.4382) and the highest in “I see no reason to avoid using social networks” (2.6304).

4. Discussion

4.1. Social Media Addiction

Parlak-Sert and Başkale (2023) found that addiction to social networks increases as students spend more time using them, reporting a significant (p < 0.05) and positive correlation between these two variables.
Similar to the findings of the present research, Soria and Villegas-Villacrés (2024) report that a 2022 survey administered in the Ecuadorian cities of Quito and Guayaquil found that WhatsApp (98.8%) and Facebook (90.4%) were the most used social networks. When grouped by gender, the results obtained by these authors showed significant differences (p < 0.01) in terms of the dimensions of social network obsession (T = 0.780), lack of personal control in social network use (T = 0.414), and excessive social network use (T = 1.751).
Aguilera-Vásconez et al. (2025) determined that among the Cuban university students who participated in their research, the preference for social networks with primary messaging services and/or access to visual entertainment content predominated, a conclusion they reached based on the following results: WhatsApp (83.6%), Facebook (79.7%), and TikTok (74.2%)—this coincided with what was observed in the present study.
In a university context in Shahada taluka, Nandurbar district, Ashhar (2024) found statistically significant differences (p < 0.01; t = 7.70) in social media addiction among students by region of origin: urban vs. rural.
In western Turkey, Sümen and Evgin (2021) analyzed social media use among high school students, finding that 49.3% had been using social media for 1 to 3 years; 53.9% were connected to social media for 1 to 3 h a day (similar to the results obtained), and 42.8% slept with their phones very close to their bodies.
Quevedo-Romero and Ponce-Delgado (2023) investigated mood states in relation to social media addiction in 254 university students, finding that there were no differences between the sexes (p = 0.762); however, they managed to statistically correlate it (p < 0.01) positively with sadness–depression (r = 0.320), anxiety (r = 0.358), and anger–hostility (r = 0.358) and to negatively correlate it with joy (r = −0.128).
In accordance with the results obtained, among 123 secondary school students in the San Francisco municipality, Zulia state, Venezuela, Cobis and Viloria (2022) made a comparison based on the number of social networks used by the students, finding statistical differences in the variable of social network addiction (p = 0.003) and its dimensions excessive use (p = 0.001) and obsession (p = 0.002). In addition, they observed a trend towards increasing levels of risk and dependence as adolescents accessed greater numbers of social networks. Likewise, they determined significant differences (p < 0.01) when grouping students according to the timing of their social media use, establishing that their use for more than five hours a day represented a higher incidence of high levels of addiction, obsession, excessive use, and lack of personal control; which coincided with the findings of the present investigation.
Condori-Sinty et al. (2023) conducted a study involving 300 students from a psychology school in Juliaca, Peru. The authors found that 17% of respondents reported having been victims of cyberbullying, although a larger number expressed concern about this danger, and they also determined a predominance of moderate levels of social media addiction and its dimensions, with frequency values ranging from 38.3% to 48.3%.
In a Mexican setting, Valencia-Ortiz et al. (2021) analyzed the frequency and duration of social media use, reporting significant differences (p ≤ 0.001) in the variables of frequency of use (t = −32.33) and hours of use per week (t = −32.83); consistent with the results obtained. These researchers concluded that students access social media less than their teachers perceive.
When comparing the perceptions of students and teachers regarding social media use, Ararat Cuberos (2017) observed significant statistical differences (p ≤ 0.001) in the following categories: communicating with friends and family (t = −31.24; g = 0.584), receiving information (t = −15.53; g = 0.385), meeting people (t = −55.952; g = 1.176), and studying and training (t = 13.91; g = 0.350), as well as significant differences in the social media that participants used (t = −37.550; g = 0.71017); Which agrees with the results obtained.

4.2. Academic Engagement

Similarly, to the results obtained in a study of 402 university students in Lima, Peru, Matalinares-Calvet et al. (2017) found significant differences (p < 0.01) in academic procrastination, accounting for the students’ social media addiction. Similarly, Morales et al. (2019) observed statistical differences in academic engagement based on leisure social media use.
Angulo-Armenta et al. (2021) state that students with greater academic commitment recognize the importance of appropriate social media use during cooperative and collaborative activities, understanding its favorable characteristics for communication among group members when taking on academic tasks.
Similar to the findings of the present research, Córdova-Gonzales et al. (2024) did not detect significant differences in academic commitment across years or semesters of enrollment (F = 3.02; p = 0.06; eta = −0.23).
In a Chilean university context in which 370 students participated, Burgos-Videla et al. (2022) compared the level of academic commitment grouped by year of enrolled study, establishing significant differences (p < 0.001) in the dimensions vigor (F = 5.35), dedication (F = 5.59), and absorption (F = 3.29). The results of the Tukey post hoc test indicated that the highest levels of dedication, vigor, and absorption were among those enrolled in the first year of the degree.
Roemer et al. (2023) found statistical differences in academic engagement across participants’ forms of social interaction in various situations, as indicated by Bonferroni–Holm p-values (k = 6).
After analyzing social media addiction in 370 Chinese university students, Zhao (2021) observed that it significantly affected subjective well-being (β = −0.387, p < 0.001). The author also established that the use of social network as entertainment constituted a significant predictive factor (β = 0.150; p < 0.05); however, this effect was adverse in the group of students without addiction (β = −0.497, p < 0.001).
Similar to what was observed in the present study, Roses et al. (2014) found no significant differences (p > 0.05) between science and humanities students in their reasons for using social media. However, science students used this resource more frequently (p < 0.05) for academic purposes, such as completing assignments, collaborating on activities, and managing doubts.

4.3. Limitation and Future Perspectives

The authors believe the main limitation of this research is the limited diversity of the population, as the programs were taught in a single area of knowledge at a single university, making it difficult to extrapolate the results. However, this characteristic facilitates a deeper understanding of this phenomenon in the studied setting, enabling an accurate diagnosis and the adoption of the most appropriate educational strategies. This study also serves as a theoretical and methodological basis for further research on the subject.

5. Conclusions

Students with sufficient academic commitment predominated in the population, as did the average level of overall social media addiction across most dimensions, except for excessive social media use, which was highly prevalent. The main variables investigated were significantly associated with one another.
Regarding the degree programs, the intergroup comparison of the level of social media addiction and its dimensions revealed statistically significant differences in the lack of control over social media use and excessive social media use. Likewise, dedication was found in the level of academic commitment and its dimensions.
When grouped by social media use, the comparison of the academic engagement levels and their dimensions showed significant differences across all the dependent variables. In contrast, in the levels of social media addiction and its dimensions, significant differences were found in the variables obsession, lack of control over social media use, and excessive social media use.
According to the frequency with which the students connected to social networks, no significant differences were found in academic commitment or its dimensions; by contrast, significant differences were found across all the dimensions of social network addiction.
Comparing the level of academic engagement and its dimensions according to social media use revealed significant differences across all the dependent variables; however, for the level of social media addiction and its dimensions, significant differences emerged in the overall level of this variable and in the level of obsession.
The groups established based on the causes for self-monitoring their social media use showed significant differences in the dimensions of academic commitment—vigor and dedication—while significant differences were found only in the obsession dimension of social media addiction.
The results enable an accurate diagnosis and the adoption of the most appropriate educational strategies, while also serving as a theoretical and methodological basis for further research on the subject.

Author Contributions

Conceptualization, Y.R.H. and D.V.T.L.; methodology, Y.R.H. and S.A.G.; validation, Y.R.H., S.A.G. and J.A.L.N.; formal analysis, Y.R.H.; investigation, Y.R.H. and S.A.G.; resources, Y.R.H. and D.V.T.L.; data curation, Y.R.H.; writing—original draft preparation, Y.R.H. and D.V.T.L.; writing—review and editing, Y.R.H., S.A.G. and J.A.L.N.; supervision, S.A.G. and J.A.L.N.; project administration, Y.R.H.; funding acquisition, Y.R.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research has not received external funding. The APC was funded by the Escuela Superior Politécnica de Chimborazo.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of UNACH Research Committee (protocol code 40-CIV-16-02-2022 and date of approval: 16 February 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data supporting the results are available upon request from the corresponding author. An anonymized dataset will be provided to anyone who requests it for academic purposes and agrees to a confidentiality agreement, subject to applicable ethical requirements.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Aguilera-Vásconez, Renata P., Luis H. Gusqui-Cayo, Pamela A. Buñay-Guisñan, Edgar G. Olivo-Silva, and José L. Guamán-Ledesma. 2025. Adicción a redes sociales y autoestima en jóvenes universitarios. Revista Habanera De Ciencias Médicas 24: E5969. [Google Scholar]
  2. Albornoz, Jorge M., Gabriela Flores-Oyarzo, Ana B. Bernardo, and Alejandro Díaz-Mujica. 2021. Correlatos conductuales del Compromiso Académico en estudiantes de Ingeniería chilenos. Trilogía Ciencia Tecnología Sociedad 13: 98–122. [Google Scholar] [CrossRef]
  3. Al-Samarraie, Hosam, Kirfi A. Bello, Ahmed I. Alzahrani, Andrew P. Smith, and Chikezie Emele. 2022. Young users’ social media addiction: Causes, consequences and preventions. Information Technology & People 35: 2314–43. [Google Scholar] [CrossRef]
  4. Angulo-Armenta, Joel, Pablo A. Sandoval-Mariscal, Carlos A. Torres-Gastelú, and Ramona I. García-López. 2021. Usabilidad de redes sociales con propósitos académicos en educación superior. Formación Universitaria 14: 25–32. [Google Scholar] [CrossRef]
  5. Ararat Cuberos, Edgar M. 2017. Análisis del uso de las redes sociales en los estudiantes universitarios de San José de Cúcuta. Colombia. Mundo Fesc 13: 106–14. [Google Scholar]
  6. Ashhar, Vajih. 2024. Social Media Addiction Among Urban and Rural College Students. International Journal of Research Culture Society 7: 62–64. [Google Scholar]
  7. Aspée, Juan, José González, and Yudi Herrera. 2021. Relación funcional entre procrastinación académica y compromiso en estudiantes de educación superior: Una propuesta de análisis. Perspectiva Educacional 60: 4–22. [Google Scholar] [CrossRef]
  8. Axelrod, Michael I., and Michael L. Santagata. 2022. Evaluating a mindfulness-based intervention to improve academic engagement. Journal of Applied School Psychology 38: 262–82. [Google Scholar] [CrossRef]
  9. Brailovskaia, Julia, and Jürgen Margraf. 2024. Addictive social media use during Covid-19 outbreak: Validation of the Bergen Social Media Addiction Scale (BSMAS) and investigation of protective factors in nine countries. Current Psychology 43: 13022–40. [Google Scholar] [CrossRef]
  10. Burgos-Videla, Carmen, Ricardo Jorquera-Gutiérrez, Eloy López-Meneses, and César Bernal. 2022. Life Satisfaction and Academic Engagement in Chileans Undergraduate Students of the University of Atacama. International Journal of Environmental Research and Public Health 19: 16877. [Google Scholar] [CrossRef]
  11. Chen, Bo-Ching, Mei-Yen Chen, Yu-Feng Wu, and Yu-Tai Wu. 2022. The relationship of social media addiction with internet use and perceived health: The moderating effects of regular exercise intervention. Frontiers in Public Health 10: 854532. [Google Scholar] [CrossRef]
  12. Cobis, Minerva, and Emily Viloria. 2022. Adicción a las redes sociales en adolescentes. Sistemas Humanos 2: 18–33. [Google Scholar] [CrossRef]
  13. Condori-Sinty, Tania, Alcides Quispe-Mamani, and Yeny Quiro-Sucapuca. 2023. Adicción a redes sociales y cansancio emocional en estudiantes Universitarios de la carrera de Psicología de una universidad privada en la ciudad de Juliaca, 2022. Revista Científica De Ciencias De La Salud 16: 18–32. [Google Scholar] [CrossRef]
  14. Córdova-Gonzales, Luis A., María E. Flores-Vásquez, Sara N. Becerra-Flores, Nicool G. Ortiz-Salazar, Josué M. Franco-Mendoza, and Rafael E. García-Vattam. 2024. Compromiso y Procrastinación Académica en Estudiantes de una Universidad Pública de Lima. Revista Científica De Salud Y Desarrollo Humano 5: 208–33. [Google Scholar] [CrossRef]
  15. Cruzat-Aliaga, Valentina. 2020. Validación de la Escala de Engagement Académico de Utrecht en estudiantes de una Universidad Chilena. Master’s thesis, Universidad de Talca, Talca, Chile. Available online: http://dspace.utalca.cl/handle/1950/12320 (accessed on 25 January 2025).
  16. de-Besa-Gutiérrez, Manuel, Facundo Froment, and Javier Gil-Flores. 2024. Credibilidad docente y compromiso académico como predictores de la satisfacción del alumnado universitario no tradicional. Revista Complutense de Educación 35: 261–72. [Google Scholar] [CrossRef]
  17. Escofet-Roig, Anna, Ana Novella-Cámara, and María V. Morín-Fraile. 2021. El codiseño como impulso del compromiso del estudiantado universitario. Aula Abierta 50: 825–832. [Google Scholar] [CrossRef]
  18. Escurra-Mayaute, Miguel, and Edwin Salas-Blas. 2014. Construcción y validación del cuestionario de adicción a redes sociales (ARS). Liberabit 20: 73–91. [Google Scholar]
  19. Froment, Facundo, and Manuel de-Besa-Gutiérrez. 2022. La predicción de la credibilidad docente sobre la motivación de los estudiantes: El compromiso y la satisfacción académica como variables mediadoras. Revista de Psicodidáctica 27: 149–57. [Google Scholar] [CrossRef]
  20. Fuster-Guillen, Fiorella G., and Jonatan Baños-Chaparro. 2021. Análisis Bayesiano del compromiso académico en estudiantes de psicología: Diferencias según sexo y edad. Revista de Investigación en Psicología 24: 5–18. [Google Scholar] [CrossRef]
  21. Gallego-Arrufat, María J., and Norma Torres-Hernández. 2025. Approach to online risk perception by Internet users. Información Tecnológica 36: 31–42. [Google Scholar] [CrossRef]
  22. Guerra-Díaz, Felipe, and Ricardo Jorquera Gutiérrez. 2021. Análisis psicométrico de la Utrecht Work Engagement Scale en las versiones UWES-17S y UWES-9S en universitarios chilenos. Revista Digital de Investigación en Docencia Universitaria 15: e1542. [Google Scholar] [CrossRef]
  23. Haseli-Songhori, Mehdi, and Kimiya Salamti. 2024. The Linkage Between University Students’ Academic Engagement and Academic Support: The Mediating Role of Psychological Capital. Iranian Journal of Educational Sociology 7: 72–84. [Google Scholar] [CrossRef]
  24. Huang, Po-Ching, Janet D. Latner, Kerry S. O’bRien, Yen-Ling Chang, Ching-Hsia Hung, Jung-Sheng Chen, Kuo-Hsin Lee, and Chung-Ying Lin. 2023. Associations between social media addiction, psychological distress, and food addiction among Taiwanese university students. Journal of Eating Disorders 11: 43. [Google Scholar] [CrossRef] [PubMed]
  25. Kelly, Yvonne, Afshin Zilanawala, Cara Booker, and Amanda Sacker. 2018. Social media use and adolescent mental health: Findings from the UK Millennium cohort study. EClinicalMedicine 6: 59–68. [Google Scholar] [CrossRef] [PubMed]
  26. Lara, Gabriela, Nicol González, Francisca Lara, Lorena Lagos, Victoria Parra, and Claudia P. Pérez-Salas. 2022. Relación docente-estudiante y compromiso escolar: Percepción de estudiantes secundarios con necesidades educativas especiales. Revista Latinoamericana de Ciencias Sociales, Niñez y Juventud 20: 164–87. [Google Scholar] [CrossRef]
  27. Lee, Michelle H. L., Manveen Kaur, Vinorra Shaker, Anne Yee, Rohana Sham, and Ching S. Siau. 2023. Cyberbullying, Social Media Addiction and Associations with Depression, Anxiety, and Stress among Medical Students in Malaysia. International Journal of Environmental Research and Public Health 20: 3136. [Google Scholar] [CrossRef]
  28. Lira-Munizaga, Juan. 2024. Comparación del compromiso académico y la desconexión académica según nivel socioeconómico de estudiantes de primer año de universidad. Wimb Lu 19: 1–18. [Google Scholar] [CrossRef]
  29. Marinoni, Carlo, Marco Rizzo, and María A. Zanetti. 2024. Social Media, Online Gaming, and Cyberbullying during the COVID-19 Pandemic: The Mediation Effect of Time Spent Online. Adolescents 4: 297–310. [Google Scholar] [CrossRef]
  30. Matalinares-Calvet, María L., Ana G. Diaz-Acosta, Luisa H. Rivas-Diaz, Alejandro S. Dioses-Chocano, Carlos A. Arenas-Iparraguirre, Ornella Raymundo-Villalba, Deyvid Baca Peruano, Joel Uceda Espinoza, Juan Yaringaño Limache, and Erika Fernandez. 2017. Procrastinación y adicción a redes sociales en estudiantes universitarios de pre y post grado de Lima. Horizonte De La Ciencia 7: 63–81. [Google Scholar] [CrossRef]
  31. Montoya-Reyes, Francisco, Juan I. Valdez-Hernández, Héctor A. Trujillo-Martínez, María T. García-Osorio, and Leonardo A. Beltrán-Rodríguez. 2024. Architecture and morphometry of Grevillea robusta A. Cunn. ex R. Br., a forest species with ornamental importance in peri-urban areas. Revista Chapingo Serie Ciencias Forestales y del Ambiente 30: 163–81. [Google Scholar] [CrossRef]
  32. Morales, Mario R., Esteban Gordon-Salcedo, Frans Noguera-Vásconez, and Santiago Morales-Cardoso. 2019. Redes sociales en universidades del país. Análisis descriptivo y planteamiento de una posible solución para mejorar el impacto en la actividad académica. Revista Cátedra 2: 16–38. [Google Scholar] [CrossRef]
  33. Morcillo-Martínez, Antonio, Álvaro Infantes-Paniagua, Andrés García-Notario, and Onofre R. Contreras-Jordán. 2021. Validación de la Versión Española de la Escala de Compromiso Académico para Educación Primaria. RELIEVE—Revista Electrónica De Investigación Y Evaluación Educativa 27: 22769. [Google Scholar] [CrossRef]
  34. Parlak-Sert, Hilal, and Hatice Başkale. 2023. Students’ increased time spent on social media, and their level of coronavirus anxiety during the pandemic, predict increased social media addiction. Health Information and Libraries Journal 40: 262–74. [Google Scholar] [CrossRef]
  35. Parra-Tijaro, Michaell, Kevin Parra-Tijaro, Juan Parra-Jiménez, Miguel A. Dimate, and Jorge M. Celis. 2022. Comparación de la Aptitud Física entre jóvenes futbolistas colombianos. Ciencias de la Actividad Física (Talca) 23: 7. [Google Scholar] [CrossRef]
  36. Pellegrino, Alfonso, Alessandro Stasi, and Veera Bhatiasevi. 2022. Research trends in social media addiction and problematic social media use: A bibliometric analysis. Frontiers in Psychology 13: 1017506. [Google Scholar] [CrossRef]
  37. Perkmann, Markus, Rossella Salandra, Valentina Tartari, Maureen McKelvey, and Alan Hughes. 2021. Academic Engagement: A Review of the Literature 2011–2019. Research Policy 50: 104114. [Google Scholar] [CrossRef]
  38. Quevedo-Romero, Carlos A., and Agueda del R. Ponce-Delgado. 2023. Adicción a las redes sociales y estado de ánimo en estudiantes universitarios: Social network addiction and mood in college students. LATAM Revista Latinoamericana De Ciencias Sociales Y Humanidades 4: 2367–79. [Google Scholar] [CrossRef]
  39. Ramírez-Gil, Esmeralda, Irma G. Cuaya-Itzcoatl, Mayte Guzmán-Pimentel, and José L. Rojas-Solís. 2021. Adicción a las redes sociales y procrastinación académica en universitarios durante el confinamiento por COVID-19. Dilemas Contemporáneos: Educación, Política y Valores 8: 00020. [Google Scholar] [CrossRef]
  40. Ramos-Vera, Cristian, Esmeralda Ayala-Laguna, and Antonio Serpa-Barrientos. 2023. Efectos de la motivación académica y de la inteligencia emocional en el compromiso académico en adolescentes peruanos de educación secundaria. Estudios Sobre Educación 45: 9–30. [Google Scholar] [CrossRef]
  41. Reeve, Johnmarshall, and Stephanie H. Shin. 2020. How teachers can support students’ agentic engagement. Theory Into Practice 59: 150–61. [Google Scholar] [CrossRef]
  42. Rigo, Daiana Y., Rosana B. Squillari, Mariela R. Caraballo, and Romina Rovere. 2021. Revisión teórica del concepto agencia: Implicancias educativas para comprender el compromiso académico; Instituto Tecnológico de Santo Domingo. Ciencia y Educación 5: 1–12. [Google Scholar] [CrossRef]
  43. Roemer, Lena, Gundula Stoll, and Matthias Ziegler. 2023. State investigative interest varies across daily life and predicts academic engagement: Replication and extension of the nomological network. European Journal of Personality 38: 441–56. [Google Scholar] [CrossRef]
  44. Roque-Herrera, Yosbanys, Santiago Alonso-García, Denys V. Tenelanda-López, and Juan A. López-Núñez. 2025. Predictive Capacity of Social Media Addiction on Academic Engagement in University Students. Education Sciences 15: 1677. [Google Scholar] [CrossRef]
  45. Rosero-Bolaños, Aldayr D., Juan S. Eraso-Meléndez, Fredy H. Villalobos-Galvis, and Harvey M. Herrera López. 2022. Validación del Cuestionario de Adicción a las Redes Sociales (ARS) en una muestra de adolescentes colombianos. Informes Psicológicos 22: 29–45. [Google Scholar] [CrossRef]
  46. Roses, Sergio, Marisol Gómez-Aguilar, and Pedro Farias. 2014. Uso académico de redes sociales: Análisis comparativo entre estudiantes de Ciencias y de Letras. Historia y Comunicación Social 18: 667–678. [Google Scholar] [CrossRef][Green Version]
  47. Sadoughi, Majid, and Yahya Hejazi. 2021. Teacher support and academic engagement among EFL learners: The role of positive academic emotions. Studies in Educational Evaluation 70: 101060. [Google Scholar] [CrossRef]
  48. Salas-Blas, Edwin, Carlo M. Vieira Ipince, and Eduardo Manzanares Medina. 2022. Adicción a las redes sociales y soledad en estudiantes universitarios limeños. Informació Psicològica 123: 2–14. [Google Scholar] [CrossRef]
  49. Saucedo-Uriarte, José Américo, Segundo M. Portocarrero-Villegas, Nancy Saldaña Gálvez, Hugo Frias, William Bardales, Luis Murga, Yander M. Briceño-Mendoza, Wigoberto Alvarado Chuqui, Gleni Tatiana Segura Portocarrero, Ilse Silvia Cayo-Colca, and et al. 2025. Texture and physicochemical analysis of Creole beef at different aging times: Differences between sex and age. Journal of Agriculture and Food Research 21: e101807. [Google Scholar] [CrossRef]
  50. Soria, Pamela, and Narcisa de J. Villegas-Villacrés. 2024. Adicción a las redes sociales y su relación con la autoestima en adolescentes. Psicología Unemi 8: 19–29. [Google Scholar] [CrossRef]
  51. Suárez-Perdomo, Arminda, Yaritza Garcés-Delgado, Edgar García-Álvarez, and Zuleica Ruiz-Alfonso. 2023. Propiedades psicométricas del cuestionario de adicción a las redes sociales (ARS) a población universitaria. Revista Española de Pedagogía 81: 361–80. [Google Scholar] [CrossRef]
  52. Sümen, Adem, and Derya Evgin. 2021. Social Media Addiction in High School Students: A Cross-Sectional Study Examining Its Relationship with Sleep Quality and Psychological Problems. Child Indicators Research 14: 2265–83. [Google Scholar] [CrossRef]
  53. Tacca-Huamán, Daniel R., Lesly K. Hernández-Huaman, Miguel A. Alva-Rodríguez, and Eduardo A. Romero-Cuellar. 2021. Propiedades psicométricas de una escala de compromiso académico en estudiantes universitarios peruanos. Revista de Investigación Psicológica 25: 11–24. [Google Scholar]
  54. Tristán-Monrroy, Beatriz V., Isabel C. Flores-Rueda, Armando Sánchez-Macías, and Guadalupe C. Briano-Turrent. 2021. Student academic engagement in times of COVID-19: Challenges and opportunities for online teaching. Formación Universitaria 14: 193–202. [Google Scholar] [CrossRef]
  55. Valencia-Ortiz, Rubicelia, Juan Cabero-Almenara, and Urtza Garay-Ruiz. 2021. Adicción a las redes sociales en estudiantes mexicanos: Percepciones de discentes y docentes. Revista Tecnología, Ciencia Y Educación 19: 103–22. [Google Scholar] [CrossRef]
  56. Vera-Muñoz, Axel O., Dayanna M. Vigo-Terán, Edwin Pajares-Huaripata, Enzo R. Bazualdo Fiorini, and Tito Urquiaga Melquiades. 2024. Adicción a las redes sociales y salud mental en estudiantes de medicina en Perú. Vive Revista de Salud 7: 475–86. [Google Scholar] [CrossRef]
  57. Wang, Jinfang, Lingrui Bu, Yan Li, Jie Song, and Na Li. 2021. The mediating effect of academic engagement between psychological capital and academic burnout among nursing students during the COVID-19 pandemic: A cross-sectional study. Nurse Education Today 102: 104938. [Google Scholar] [CrossRef]
  58. Wang, Xu, Yan L. Liu, Bin Ying, and Jie Lin. 2023. The effect of learning adaptability on Chinese middle school students’ English academic engagement: The chain mediating roles of foreign language anxiety and English learning self-efficacy. Current Psychology 42: 6682–92. [Google Scholar] [CrossRef]
  59. Zhao, Lei. 2021. The impact of social media use types and social media addiction on subjective well-being of college students: A comparative analysis of addicted and non-addicted students. Computers in Human Behavior Reports 4: 100122. [Google Scholar] [CrossRef]
  60. Zhu, Qianyu, Yeram Cheong, Cixin Wang, and Jiajin Tong. 2021. The impact of maternal and paternal parenting styles and parental involvement on chinese adolescents’ academic engagement and burnout. Current Psychology 42: 2827–40. [Google Scholar] [CrossRef]
Table 1. Population distribution according to enrollment characteristics.
Table 1. Population distribution according to enrollment characteristics.
CarreraSemesterTotal
FirstSecondThirdFourthFifthSixth
Clinical Psychologyn42416283826181
%3.53.40.52.33.22.215.1
Medicinen25594832583243
%2.14.94.00.22.16.920.2
Nursingn586020303643247
%4.85.01.72.53.03.620.6
Clinical Laboratoryn413638273226200
%3.43.03.22.22.72.216.7
Physical therapyn28382223648165
%2.33.21.81.90.54.013.8
Dentistryn5421466289164
%4.51.83.80.52.30.813.7
Totaln2482551801171652351200
%20.721.215.09.813.819.6100.0
Table 2. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on career.
Table 2. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on career.
VariableSum of SquaresglMean SquareFSig.
Level of Academic Commitment
Global6.39851.2801.7160.128
Vigor7.11051.4221.8160.107
Dedication10.98652.1972.3640.038 *
Absorption6.72251.3441.7880.112
Level of Addiction to Social Network Use
Global0.49150.0981.5600.168
Obsession1.73750.3471.3940.224
Lack of use control3.92950.7862.7920.016 *
Excessive use5.76751.1533.9260.002 **
Note: ** Statistically significant at p < 0.01; * statistically significant at p < 0.05.
Table 3. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on the social networks used by the participants.
Table 3. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on the social networks used by the participants.
VariableSum of SquaresglMean SquareFSig.
Level of Academic Commitment
Global9.86233.2874.4330.004 **
Vigor12.95534.3185.5600.001 **
Dedication21.19937.0667.6870.000 **
Absorption8.39432.7983.7340.011 *
Level of Addiction to Social Network Use
Global0.24030.0801.2670.284
Obsession2.25830.7533.0300.028 *
Lack of use control3.78431.2614.4860.004 **
Excessive use4.82531.6085.4680.001 **
Note: ** Statistically significant at p < 0.01; * statistically significant at p < 0.05.
Table 4. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on the frequency of social network connection.
Table 4. Comparison of the levels for the main variables and their corresponding dimensions, grouped based on the frequency of social network connection.
VariableSum of SquaresglMean SquareFSig.
Level of Academic Commitment
Global7.09851.4201.9050.091
Vigor6.88851.3781.7590.118
Dedication5.74551.1491.2300.292
Absorption8.07251.6142.1500.057
Level of Addiction to Social Network Use
Global0.54950.1101.7460.121
Obsession9.33551.8677.6880.000 **
Lack of use control12.92052.5849.4330.000 **
Excessive use17.80953.56212.5540.000 **
Note: ** Statistically significant at p < 0.01.
Table 5. Comparison of the levels of the main variables and their corresponding dimensions, grouped based on the population’s social network use.
Table 5. Comparison of the levels of the main variables and their corresponding dimensions, grouped based on the population’s social network use.
VariableSum of SquaresglMean SquareFSig.
Level of Academic Commitment
Global21.75145.4387.4270.000 **
Vigor23.54945.8877.6610.000 **
Dedication21.98245.4955.9770.000 **
Absorption17.00444.2515.7240.000 **
Level of Addiction to Social Network Use
Global0.81740.2043.2610.011 *
Obsession3.13040.7833.1580.014 *
Lack of use control1.76840.4421.5620.182
Excessive use2.10540.5261.7740.132
Note: ** Statistically significant at p < 0.01; * statistically significant at p < 0.05.
Table 6. Comparison of the levels of the main variables and their corresponding dimensions, grouped based on causes to self-control social media use.
Table 6. Comparison of the levels of the main variables and their corresponding dimensions, grouped based on causes to self-control social media use.
VariableSum of SquaresglMean SquareFSig.
Level of Academic Commitment
Global9.02561.5042.0220.060
Vigor13.60762.2682.9150.008 **
Dedication14.65962.4432.6350.015 *
Absorption9.29661.5492.0650.055
Level of Addiction to Social Network Use
Global0.32060.0530.8450.535
Obsession4.57060.7623.0830.005 **
Lack of use control2.34760.3911.3820.219
Excessive use3.12860.5211.7600.104
Note: ** Statistically significant at p < 0.01; * statistically significant at p < 0.05.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Roque Herrera, Y.; Alonso García, S.; Tenelanda López, D.V.; López Núñez, J.A. Levels of Academic Engagement and Social Media Addiction Among University Students: A Comparative Study. Soc. Sci. 2026, 15, 49. https://doi.org/10.3390/socsci15010049

AMA Style

Roque Herrera Y, Alonso García S, Tenelanda López DV, López Núñez JA. Levels of Academic Engagement and Social Media Addiction Among University Students: A Comparative Study. Social Sciences. 2026; 15(1):49. https://doi.org/10.3390/socsci15010049

Chicago/Turabian Style

Roque Herrera, Yosbanys, Santiago Alonso García, Dennys Vladimir Tenelanda López, and Juan Antonio López Núñez. 2026. "Levels of Academic Engagement and Social Media Addiction Among University Students: A Comparative Study" Social Sciences 15, no. 1: 49. https://doi.org/10.3390/socsci15010049

APA Style

Roque Herrera, Y., Alonso García, S., Tenelanda López, D. V., & López Núñez, J. A. (2026). Levels of Academic Engagement and Social Media Addiction Among University Students: A Comparative Study. Social Sciences, 15(1), 49. https://doi.org/10.3390/socsci15010049

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop