Investigating Mental Health Literacy and Its Relationship with Addiction to Social Networks among Allied Medical Sciences Students

Mohammad Azimi Tabas ¹, Maryam Kazerani ^1,*, Azam Shahbodaghi ¹, Reza Taherian ²

1. Department of Medical Library and Information Science, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2. Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

* Correspondence: Maryam Kazerani

Academic Editor: Bart Ellenbroek

Received: June 24, 2025 | Accepted: November 13, 2025 | Published: November 19, 2025

OBM Neurobiology 2025, Volume 9, Issue 4, doi:10.21926/obm.neurobiol.2504311

Recommended citation: Tabas MA, Kazerani M, Shahbodaghi A, Taherian R. Investigating Mental Health Literacy and Its Relationship with Addiction to Social Networks among Allied Medical Sciences Students. OBM Neurobiology 2025; 9(4): 311; doi:10.21926/obm.neurobiol.2504311.

© 2025 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

1. Introduction

The pervasive use of social media among college students has raised significant concerns regarding its impact on mental health and the potential for addictive behaviors. As digital platforms become integral to daily life, they present both opportunities for connection and risks for psychological well-being. Research indicates that social media can lead to increased levels of internet addiction, anxiety, and depression, particularly among young adults who are navigating the pressures of academic life and social expectations [1]. College students are particularly susceptible to the adverse effects of social media due to their high engagement levels and the transitional nature of their lives. This demographic often experiences unique stressors, such as academic pressures, social comparisons, and the need for peer acceptance [2]. Studies have shown that a significant percentage of college students report symptoms associated with social media addiction, which correlates with poorer mental health outcomes [3].

On the other hand, mental disorders are prevalent worldwide and have become a significant concern for healthcare systems. Recent global socioeconomic changes, such as industrialization, rapid population growth, urbanization, and migration, have contributed to the increase in these disorders in various communities [4]. These disorders can significantly reduce the quality of life and impose considerable economic and social burdens on individuals, families, and communities. As a result, managing mental disorders has become a top priority for many countries and has garnered significant attention from researchers and policymakers [5]. Due to the high prevalence, chronic nature, and long-term negative consequences of these disorders, there is an urgent need for continuous monitoring of the population's mental health and the implementation of effective control strategies. One such strategy is promoting health literacy, particularly mental health literacy, which has been shown to have a positive impact at the community level [6].

Mental health literacy (MHL) refers to the understanding and awareness of mental disorders, including their symptoms, management, and prevention [7]. This concept comprises three interconnected elements: knowledge, attitudes, and help-seeking behaviors [8]. In recent years, the low level of MHL has emerged as a significant concern [7]. Studies show that the general population, especially young people, has low levels of MHL [7,9]. Moreover, mental health problems are often associated with stigma and shame, even among young individuals [10]. Low levels of MHL pose a significant challenge in the treatment of mental disorders [11]. However, research indicates that improving MHL can effectively enhance mental health [9]. By increasing knowledge about mental health and mental disorders, individuals can detect mental disorders earlier, become more aware of how to seek help and treatment, and reduce mental illness symptoms at the individual, social, and institutional levels. This leads to improved mental health outcomes and increased use of psychiatric services [12]. Overall, raising public awareness about detecting disorders through MHL is linked to better social functioning and quality of life.

Although research on mental health literacy has examined several mental disorders to date, very little attention has been given to behavioral addictions [13]. One type of behavioral addiction is addiction to social networks. With the rise of mobile technologies and the widespread use of smartphones, accessing the internet has become easier. As a result, social networks have become increasingly popular among teenagers and young people [14]. Social networks are virtual spaces where users can connect with friends and others by creating personal accounts and engaging in virtual interactions based on their interests [15]. However, addiction to social networks (ASNs) is a global issue [16]. This addiction, or pathological use of social networks, occurs when compulsive engagement in social media platforms significantly disrupts the users' functioning in important life domains, such as interpersonal relations, work or study performance, and physical health [17]. In Iran, the prevalence of internet addiction has been reported to be 3.8% among high school students, 10.8% among medical students, and 22.8% among general internet users [18]. Excessive use of social networks can lead to changes in lifestyle, including alterations in interactions and communications among young people [19].

Previous research in this field has focused primarily on the relationship between mental health and IA. Findings from these studies suggest a significant correlation between mental health and internet addiction [20,21]. For instance, one study found that students addicted to the internet were at a greater risk of developing mental illnesses than were regular internet users [22]. Furthermore, ASN can contribute to cognitive disorders such as stress and depression [23]. However, no study has investigated the relationship between MHL and ASN, leaving this relationship unclear. Therefore, further research is necessary to explore this issue.

In light of this research gap, our study aimed to examine the relationship between mental health literacy and social network addiction among students at the School of Allied Medical Sciences. The results of this research can provide valuable insights into the state of MHL and ASN in the studied population. Policymakers and health authorities can use this information to plan effectively to improve MHL and prevent ASN.

2. Materials and Methods

2.1 Participants and Study Design

This study was a cross-sectional investigation involving 177 students enrolled in bachelor's, master's, and PhD programs at the School of Allied Medical Sciences at SBMU in 2023.

2.2 Sampling and Power Analysis

Stratified random sampling based on gender and educational level was used to select participants. Considering an average effect size of 0.30 for the correlation between mental health literacy and social media addiction, a confidence level of 95%, and a power of 90%, the sample size was determined to be at least 120 people using GPower software (3.1.9.7). Inclusion criteria: must be a student in one of the "allied medical sciences" programs offered by the school, with availability and consent. Exclusion Criteria: Non-Students: faculty, staff, and administrative personnel of the school were excluded. Students from Other Schools/colleges were excluded. The study was strictly limited to the School of Allied Medical Sciences. Inability to participate: Unavailable Students (e.g., on leave, absent) or unwilling to participate were effectively excluded. In this study, 200 questionnaires were distributed among students. Of these, 23 were excluded due to incompleteness, leaving a final sample of 177 students.

2.3 Data Collection

Before approaching the students, an ethical code (IR.SBMU.RETECH.REC.1402.110) was obtained from the Vice-Chancellor of Research Affairs in SBMU. Then the researcher went to the School of Allied Medical Sciences at SBMU, introduced himself to students on break, and explained the purpose of the study. If the students expressed their desire and initial consent to complete the questionnaire, additional explanations were provided to answer the questions in a safe place for more concentration. The majors of participants were radiology, medical laboratory science, health Information management, hematology, biostatistics, medical library, and information science. The questionnaires were completed in the presence of the researcher in about 12 minutes and then collected so that if they had any questions or doubts about completing the questionnaire, they could ask the researcher.

2.4 Measures

Data were collected using two questionnaires in addition to a sociodemographic questionnaire: the Mental Health Literacy Questionnaire (MHLQ) and the Addiction to Social Networks Questionnaire (ASNQ). The MHLQ, initially developed by Campos, et al. in 2016 [24] and adapted to Persian by Zarebi et al., assesses students' MHL. It consists of 29 questions in 4 dimensions, including awareness of mental health problems (D1) via 14 questions, incorrect beliefs about mental health problems (D2) via 8 questions, help-seeking (D3) via 3 questions, and self-help strategies (D4) via 4 questions. It was rated on a 5-point Likert scale, with a total score ranging from 29 to 145. The compound reliability for all subscales in this questionnaire was greater than 0.5, indicating the scale's desired reliability. CVR was more than 0.62 percent, and the CVI was more than 0.75 percent, indicating the appropriate content validity of the scale [25]. Since the questionnaire does not provide qualitative categorization for MHL scores, the researcher utilized feedback from mental health experts and statistical experts to select 50% and 75% as cutoff points for MHL scores. This categorization allows responses to be classified as "insufficient", "moderate", or "sufficient". Using 50% as a midpoint and 75% as a higher threshold ensures a uniform distribution of responses among categories. Statistically, 50% can represent the median (second quartile), and 75% can represent the third quartile. This can help capture different levels of responses in the data. Additionally, 50 and 75 are easily recognizable and intuitive numbers, making it easier for researchers and readers to interpret the results. Based on these cutoff points, MHL is described on a 5-point Likert scale as insufficient (29-86), moderate (87-115), or sufficient (116-145).

To measure ASN among students, we used the ASNQ, developed by Khajeahmadi et al. [26] in 2017 based on Waltz's four-step method [27]. The questionnaire was classified into four factors, including individual performance (F1) via 9 questions, time management (F2) via 6 questions, self-control (F3) via 4 questions, and social communication (F4) via 4 questions, with a prediction capability of 57.470. The internal reliability coefficient was α = 0.92. Responses are categorized on a 5-point Likert scale, with the level of ASN described in four levels: lower than average user (23-46), average user (46-69), user on the verge of addiction (69-92), and addicted user (92-115). The total score of the questionnaire ranges from 23 to 115.

2.5 Data Analysis

In the present study, the data were analyzed by SPSS software (version 28). The normality of the data was tested using the Shapiro‒Wilk test (P value > 0.05). Descriptive statistical methods, such as frequency distribution tables, means, and standard deviations, were used based on the research objectives and types of variables. Differences in mental health measures were explored using analyses of variance for demographic variables. To examine relationships between measures (MHLQ and ASNQ), Pearson correlations were used. The statistical significance and power levels were set at 0.05 and 90%, respectively. Additionally, linear regression models were used to examine the relationships between demographic variables and MHLQ and ASNQ scores. Demographic variables included marital status (due to differences in social media usage), income level (due to easier access to information), education level (due to greater academic and clinical knowledge), gender (due to differences in information-seeking behaviors), and age (due to different attitudes toward technology).

2.6 Ethical Consideration

This study was derived from a Master's thesis in the School of Allied Medical Sciences at SBMU, under the ethical code IR.SBMU.RETECH.REC.1402.110 available in: https://ethics.research.ac.ir/IR.SBMU.RETECH.REC.1402.110.

3. Results

Of the 177 participants, 107 (60.5%) were female, and 70 (39.5%) were male. Additionally, 130 participants (73.5%) were studying at the bachelor's level, 28 (15.8%) at the master's level, and 19 (10.7%) at the PhD level. Furthermore, 135 participants (76.3%) were single, 42 (23.7%) were married, 90 (50.8%) had income, and 87 (49.2%) had no income. Among those with income, 24 participants (13.6%) were unsure whether their income was sufficient, 49 (27.7%) considered it somewhat enough, and 17 (9.6%) considered it completely enough (Table 1).

Table 1 Demographic characteristics of the participants (N = 177).

The overall average score for MHL among the students was 93.48 ± 21.52, which is moderate (Table 2).

Table 2 Mental Health literacy rates in the participants.

The majority of the study participants had moderate MHL (95 participants, 53.7%); 66 participants (37.3%) had insufficient MHL; and 16 participants (9.0%) had sufficient MHL. The overall average MHL score was 90.48 ± 17.65 for men and 93.12 ± 16.37 for women. Furthermore, the overall average mental MHL score of bachelor's students was 88.79 ± 16.64, that of master's students was 97.28 ± 13.60, and that of PhD students was 106.89 ± 13.17 (P < 0.05) (Table 3).

Table 3 The level of MHL according to gender and educational level in students at the School of Allied Medical Sciences.

The overall average ASN score among the students was 63.96 ± 19.22 (Table 4).

Table 4 Addiction to Social Networks rates among participants.

In terms of addiction, the majority of study participants were at an average level (77 participants, 43.5%), followed by users on the verge of addiction (54 participants, 30.5%), users at a lower than average level (34 participants, 19.2%), and addicted users (12 participants, 6.8%). The overall average ASN in men was 66.12 ± 18.13, and that in women was 62.55 ± 19.86 (P < 0.05) (Table 5).

Table 5 The level of ASN according to gender and educational level in students of the School of Allied Medical Sciences.

The results of the correlation test for measuring the relationship between the dimensions (as explained in the methodology section) of MHL (D1, D2, D3, D4) and ASN (F1, F2, F3, F4) in participants, using the Pearson correlation coefficient, are presented in Table 6. There is a significant negative relationship between mental health literacy and addiction to social networks in all dimensions.

Table 6 Correlation matrix between dimensions of MHL and ASN.

There is a significant negative correlation between mental health literacy and addiction to social networks; the correlation coefficient (r = -0.767) was statistically significant (P-value < 0.001). This finding shows that as mental health literacy increases, the likelihood of social network addiction decreases (Table 7).

Table 7 The relation between MHL & ASN.

In the first part of Table 8, where the MHL score was considered the response variable, marital status, income, and master's degree education were statistically significant. Based on the regression coefficients, being married, higher income, and higher educational level were associated with higher MHL scores. Specifically, on average, compared with single individuals, married individuals had an 11.099 higher score in MHL, students with monthly income had a 5.571 higher score in MHL than did students without income, and students in master's and PhD programs had 9.773 and 16.611 higher scores in MHL, respectively, than did bachelor's students (no significant difference was observed between master's and PhD students). No significant associations were found between age or gender and MHL (Table 8). In the second part of Table 8, where the ASN score was considered the response variable, marital status, income, and master's degree education were statistically significant. According to the obtained regression coefficients, these variables hurt the ASN score. In other words, on average, married individuals had a 17.312 lower ASN score than single individuals, students with a monthly income had a 6.512 lower ASN score than individuals without income, and master's students had a 9.941 lower ASN score than did bachelor's students (no significant difference was observed between PhD students and master's students). No significant associations were found between age or gender and ASN (Table 8).

Table 8 Results of the multiple regression analysis of the relationship between the demographic variables, MHL, and ASN.

4. Discussion

Mental health literacy has been described as knowledge and beliefs about mental disorders that help their recognition, management, and prevention [28]. Also, prevention of addiction to social networks is an essential topic in health service education [29]. Using social media networks too frequently can make people feel increasingly unhappy and isolated [30]. The lack of mental health literacy has been cited as one of the most critical problems in the treatment of mental disorders, such as social network addiction [31]. Nowadays, the majority of college students obtain health-related information from the internet and social media, potentially exposing them to significant amounts of inaccurate information. It is clear that health misinformation poses a danger and can compromise individuals' physical and mental well-being [32].

The results of this study indicate that the overall average MHL among allied medical sciences students is moderate. This finding is consistent with previous research by Bahrami et al. [33]. This study aimed to investigate the correlation of MHL and general health among Iranian female students. It was a cross-sectional study conducted during the first 6 months of 2018 among students at an Iranian high school. A total of 65 students contributed to the study. Data were gathered using two valid questionnaires, Goldberg and Hillier's version of the General Health Questionnaire (GHQ-28), to measure psychological quality of life, and the Depression Literacy Questionnaire (D-Lit). The study found that participants have a moderate level of MHL.

Similarly, Almanasef [34], which examined mental health literacy among undergraduate pharmacy students, reported an overall average MHL of 112.53 (range 35-160), which is also in line with the results of this study. It was a prospective cross-sectional study that used an online self-administered questionnaire during 2019-2020. A total of 271 pharmacy students at King Khalid University completed the questionnaire and agreed to participate in the study.

In contrast, studies conducted in the UK [35] have reported that Mental health literacy in the students sampled was lower than seen in previous research. The purpose of this study was to ascertain levels of mental health literacy in UK university students during 2015-2016. A total of 380 university students at a university in southern England completed online surveys measuring multiple dimensions of mental health literacy.

Furthermore, only 9% of the participants in this study had sufficient MHL, which is consistent with the findings of Jafari et al. [36]. This cross-sectional study aimed to determine the status of mental health literacy (MHL) and its relationship with the quality of life across the Iranian general population. Using a multi-stage sampling method, 1070 participants were selected from the city of Gonabad (Iran). The data collection period was from October 2020 to January 2021. The mean and standard deviation of the total score of MHL were 113.54 and 10.34 (out of 160), and most people did not have a high level of MHL.

Other studies have also reported inadequate levels of MHL among various groups. For instance, Nguyen [37] reported that Vietnamese students lacked sufficient MHL. This cross-sectional study aimed to investigate the MHL of depression among public health and sociology undergraduate students in Hanoi, Vietnam. It was conducted from May to September 2015. Data were collected using an anonymous, self-administered questionnaire distributed to 350 undergraduate students (213 public health majors; 137 sociology majors). Questions about MHL of depression were adapted from the Australian National Survey of Mental Health Literacy and Stigma. Overall, mental health literacy of depression among the undergraduate students surveyed in this study was not as high as in other countries.

While Lam [38] reported that only 16% of adolescents had a sufficient level of MHL, this population-based health survey was conducted in China in October 2013. The Australian National Mental Health Literacy scale measured mental health literacy. The results showed an inadequate mental health literacy among research participants.

Taken together, these results suggest an urgent need to improve MHL across all societies, regardless of geographic differences. Educational interventions, including appropriate educational programs, may be necessary to address this issue.

According to this study's results, the majority of individuals surveyed are regular users of ASN. These findings are consistent with previous research by Movahhed et al. [39]. One aim of this study was to investigate the rate of mobile-based social network addiction in women living in Ghaen city. Data collection tools in this part of the study were the Social Media Addiction Questionnaire of Khajeh Ahmadi et al. [26]. The mean and standard deviation of the variable on addiction to mobile-based social networks were 51.63 and 20.78, respectively, among 112 participants (maximum rate).

In a study conducted by Komeili Sani et al. [40] in the faculty of medical Science, Shoushtar, Iran, in 2016, with a researcher-designed questionnaire of addiction to social networks, the level of ASN was found to be moderate in 60.8% of students, which is consistent with the results of this study.

However, in the study by Kahoui et al. [41], which involved 350 students at Semnan University of Medical Sciences. In 2019, a mobile-based social network addiction questionnaire, 53.2% of the students were addicted to social networks, which contradicts the findings of this study.

Additionally, Sujarwoto et al. [42] reported a general average addiction rate to social networks of 16.79% (range 6-24) among Indonesian students, indicating a high level of ASN, which is not in line with the results of this study. They collected data using Bergen Social Media Addiction Scale (BSMAS) from 709 students at universities across the country between June 3 and June 20, 2020. It could be argued that this study was conducted during COVID-19, when people should have applied for web facilities more than usual, so this condition may have affected the ASN level of students.

However, considering the results of our study, more than one-third of the individuals surveyed were addicted or were on the verge of addiction, which is consistent with the findings of Komeili Sani et al. [40]. In light of these findings and considering the potential consequences of ASN, including excessive screen time, compulsive checking, and detrimental effects on real-life relationships and responsibilities [43], it is necessary for officials, particularly those involved in the educational system, to pay more attention to this phenomenon. The mental and physical health of students as a productive sector of society must be prioritized [44].

This study revealed a significant negative correlation between MHL and ASN across all dimensions (Table 6). While most previous studies have reported a significant negative relationship between mental health (not MHL) and internet addiction [20,21,42,45], this study is the first to specifically investigate the relationship between MHL and ASN. The results suggest that increasing MHL can significantly reduce ASN; in other words, essentially, high MHL acts as a protective shield, fostering the self-awareness and coping skills needed to navigate social media's addictive design healthily. At the same time, low MHL can leave an individual vulnerable to falling into a vicious cycle of addiction and deteriorating mental health. As such, those in positions of responsibility can help reduce and prevent ASN by providing accessible information about mental health and increasing students' MHL. Furthermore, leveraging the expertise of librarians in searching for and evaluating relevant information can significantly increase MHL [46] and consequently prevent ASN.

This study revealed a significant relationship between MHL and marital status among students, with married individuals having higher MHL than single individuals. Also, a significant relationship was found between MHL and income among the study participants. This finding is consistent with Schneider et al. [47] in Zurich, who reported that nearly half of respondents had low MHL levels, particularly those with higher age and greater financial deprivation.

This study revealed a significant relationship between ASN and marital status among students. Compared with married individuals, single individuals were found to have greater levels of ASN, which is consistent with the findings of Ozbek and Caras [48] in Turkey. In contrast, no significant relationship was found between ASN and age among the study participants. This contradicts the findings of Kahouei et al. [41], who reported higher levels of ASN among younger individuals. Similarly, studies by Andreassen et al. [49] in Norway and Luo et al. [50] in China also reported higher levels of ASN among younger individuals, which is inconsistent with the results of this study. Additionally, no significant relationship was found between ASN and gender among the study participants. This contradicts the findings of Kahouei et al. [41] and Ozbek and Karas [48], who reported higher levels of ASN among men than among women. In contrast, Andreassen et al. [49] found higher levels of ASN among women in Norway, findings that are inconsistent with this study's results. Finally, a significant relationship between ASN and income was found among the study participants. Individuals with income were found to have lower levels of ASN than those without income. This is consistent with the findings of Luo et al. [50] in China, who reported that individuals with greater financial satisfaction have lower levels of ASN. Similarly, Andreassen et al. [49] reported that individuals with lower income have greater levels of ASN, while Ozbek and Karas [48] reported that individuals with higher income have lower levels of ASN in Turkey, both of which are in line with the results of this study.

According to the results, since most students acquire health-related information online and through social networks, they may be exposed to a vast amount of incorrect information. Misinformation on social media platforms is a global concern [51]. It is evident that inaccurate health information is harmful and can jeopardize individuals' physical and mental health.

The limitations of this research included a negative attitude toward mental disorders in society, which restricted the cooperation of individuals in conducting this research. Additionally, this study had a small sample size, and most participants were young. It is recommended that further studies with larger sample sizes and different age groups be conducted. It is also suggested that more studies be conducted on students from various academic fields.

5. Conclusion

The findings indicate that while students exhibit a moderate level of mental health literacy, this knowledge is inversely related to their addiction to social networks. Enhancing mental health literacy emerges as a vital strategy for empowering students to make informed decisions regarding their social media use, thereby reducing the risk of addiction and its associated mental health issues, such as anxiety and depression. The study advocates for targeted interventions aimed at improving mental health literacy as a preventive measure against the adverse effects of excessive social media engagement, ultimately fostering healthier online behaviors among college students. Establishing facilities for benefiting from mental health literacy components, such as training classes, familiarity with web facilities in the field of mental health, identification of correct information in the web environment, and use of library educational platforms, may help prevent addiction to social networks.

Acknowledgments

The researchers would like to thank all the students who participated in this research project.

Author Contributions

Mohammad Azimi Tabas: contributed to the provision and collection of the data, also conceptual design. Maryam Kazerani: contributed to the critical revision of the manuscript, as well as the final approval of the study, and supervised the study. Azam Shahbodaghi: contributed to the study as an advisor. Reza Taherian: contributed to data analysis.

Funding

All authors declare that they have no source of funding.

Competing Interests

All Authors disclose that there is no conflict of interest at the time of submission, information on financial issues, or other matters that may influence the manuscript. None of the authors has a conflict of interest to disclose.

AI-Assisted Technologies Statement

The authors utilized Grammarly, an AI-powered writing assistant, for grammar checking, punctuation, and style enhancement in the preparation of this manuscript. The content, research, ideas, and intellectual contributions remain solely the responsibility of the authors.