This study explored the impact of smartphone usage on attention span among 150 college students, focusing on usage duration, purpose (academic, recreational, social), and intensity (light, moderate, heavy). Employing a quantitative-correlational design, data were gathered through a structured questionnaire and the Mindful Attention Awareness Scale (MAAS). Descriptive statistics revealed that the majority of participants were moderate to heavy smartphone users, with a high preference for social and recreational use over academic purposes. Correlational analysis indicated a significant negative relationship between smartphone usage and attention span (r = -0.42, p < 0.01), suggesting that increased smartphone use is associated with reduced attention. ANOVA results showed statistically significant differences in attention span based on both the type and intensity of smartphone usage (p < 0.05), with recreational and heavy users exhibiting notably lower attention scores compared to academic and light users. These findings highlight the cognitive risks of excessive smartphone engagement and support the implementation of digital well-being interventions in academic settings. Future research should examine longitudinal outcomes and consider psychological moderators such as self-regulation and mindfulness.
EXPLORING THE RELATIONSHIP BETWEEN SMARTPHONE USAGE AND ATTENTION SPAN AMONG COLLEGE STUDENTS IN THE DIGITAL ERA
Josephine P. Manapsal, Ph.D, RPsy, LPT
Abstract
This study explored the impact of smartphone usage on attention span among 150 college students, focusing on usage duration, purpose (academic, recreational, social), and intensity (light, moderate, heavy). Employing a quantitative-correlational design, data were gathered through a structured questionnaire and the Mindful Attention Awareness Scale (MAAS) . Descriptive statistics revealed that the majority of participants were moderate to heavy smartphone users, with a high preference for social and recreational use over academic purposes. Correlational analysis indicated a significant negative relationship between smartphone usage and attention span (r = -0.42, p < 0.01), suggesting that increased smartphone use is associated with reduced attention. ANOVA results showed statistically significant differences in attention span based on both the type and intensity of smartphone usage (p < 0.05), with recreational and heavy users exhibiting notably lower attention scores compared to academic and light users. These findings highlight the cognitive risks of excessive smartphone engagement and support the implementation of digital well-being interventions in academic settings. Future research should examine longitudinal outcomes and consider psychological moderators such as self-regulation and mindfulness.
Keywords: smartphone usage, attention span, MAAS, cognitive focus, academic performance, digital behavior, mobile technology, college students
Introduction
The digital era has revolutionized how people access information, communicate, and engage with the world. Among the most significant innovations is the smartphone—a ubiquitous device that offers instant access to news, social media, entertainment, and educational resources. College students, in particular, are among the most avid users of smartphones, relying on them for academic, social, and personal purposes. While the benefits of smartphone usage are widely acknowledged, growing concerns have emerged regarding its potential impact on cognitive functions, especially attention span (Wilmer, Sherman, & Chein, 2022).
Attention span—the ability to focus on a task without being distracted—is a critical cognitive skill for academic success. However, increasing evidence suggests that excessive or multitasking smartphone use may lead to shorter attention spans, cognitive overload, and reduced academic performance (Jiang et al., 2021; Gazzaley & Rosen, 2022). With college students being digital natives who spend significant hours on their devices daily, understanding how their attention span is influenced by smartphone usage is essential in crafting evidence-based strategies to promote healthier digital habits and enhance academic outcomes.
The rapid development of mobile technology, especially after the COVID-19 pandemic, has further increased reliance on smartphones. Remote learning, online assessments, and digital collaboration tools have made smartphones essential academic tools (Mei et al., 2023). Yet, this increased dependency comes with challenges. Students often find themselves distracted by notifications, social media, and entertainment apps, even during classes or study sessions. This dual-use nature—where smartphones can be both helpful and harmful—makes it critical to examine how specific patterns of usage relate to students' ability to maintain attention.
Moreover, modern smartphones are designed to maximize user engagement through persuasive technologies such as infinite scrolling, autoplay, and algorithmic content personalization. These features, while enhancing user experience, are also linked to compulsive checking behaviors and attentional fragmentation (Hadlington & Murphy, 2021). Studies have indicated that frequent switching between tasks—also known as media multitasking—can impair the brain’s ability to filter out irrelevant information, leading to a reduction in sustained attention and working memory capacity (Gazzaley & Rosen, 2022). Such findings warrant an exploration of whether attention-related problems observed in academic settings may be partly attributed to digital habits.
Despite ongoing research, many studies focus broadly on screen time or digital addiction, without distinguishing between various smartphone use contexts—educational, social, or recreational. This creates a need for more nuanced research that goes beyond total usage time to examine how different types of smartphone activities impact attention span. Furthermore, most empirical studies are conducted in Western countries, leaving a gap in understanding how smartphone usage impacts students in non-Western, collectivist cultures such as the Philippines, where digital engagement patterns and academic pressures may differ significantly (Kates, Wu, & Coryn, 2022).
Additionally, there is limited discussion in the literature on how individual differences such as self-regulation, time management, and academic motivation moderate the relationship between smartphone use and attention span. Some students may be more resilient to digital distractions, while others may be more vulnerable to cognitive disruptions caused by excessive use. By investigating these individual and contextual variables, this study seeks to uncover patterns that may inform tailored interventions for college students facing attentional challenges due to smartphone habits.
Lastly, in a society where digital fluency is often mistaken for digital literacy, college students may not always be aware of the cognitive consequences of their smartphone behaviors. Educators, parents, and mental health professionals need a clearer picture of how students' technology use affects their learning capacities. By exploring the relationship between smartphone usage and attention span, this study aims to contribute not only to academic literature but also to the development of informed strategies that promote cognitive wellness and academic achievement in an increasingly digital world.
Background of the Study
The widespread adoption of smartphones over the past two decades has fundamentally changed the landscape of communication, information access, and social interaction. What began as a tool for convenience and connectivity has evolved into a digital hub that seamlessly integrates entertainment, academic resources, social networking, and productivity tools. For college students in particular, smartphones are no longer optional devices—they are necessities embedded into daily routines. From accessing virtual learning platforms and conducting online research to managing schedules and maintaining social connections, smartphones have become deeply intertwined with students' academic and personal lives (Statista, 2023).
However, with the increasing functionality and appeal of smartphones comes the challenge of managing their use in ways that support rather than hinder cognitive and academic performance. A growing body of psychological and educational research has raised concerns about the negative cognitive implications of excessive or unregulated smartphone usage, particularly its impact on attention span. Attention span refers to the duration an individual can maintain focus on a task without being distracted. It is a core element of executive function that underpins successful learning, memory retention, and academic achievement (Wilmer, Sherman, & Chein, 2022).
Attention-related issues among students have been observed in various academic settings, with many educators reporting a noticeable decline in students' ability to concentrate, sustain engagement, and complete tasks efficiently. One frequently cited factor is the omnipresence of smartphones, which provide constant access to digital stimuli such as notifications, social media updates, videos, and games. Research by Hadlington and Murphy (2021) suggests that frequent smartphone interruptions contribute to attentional fragmentation—where users experience difficulty maintaining focus for extended periods due to repeated switching between tasks and screens.
Moreover, the COVID-19 pandemic intensified the reliance on smartphones as remote learning became the norm for many college students. While smartphones enabled continued education during periods of lockdown and campus closure, they also blurred the boundaries between academic and leisure use. Students began using the same device for watching lectures, messaging friends, streaming content, and scrolling through social media—all within the same hour. This blending of functional and recreational use complicates the way attention is allocated, often leading to cognitive fatigue and reduced academic productivity (Mei et al., 2023).
Despite these concerns, smartphones also serve as tools for enhancing productivity and learning when used intentionally. Apps designed for organization, note-taking, language learning, and time management can aid students in achieving their academic goals. Some researchers have even suggested that digital media can improve certain aspects of attention, such as scanning for information or multitasking (Kates, Wu, & Coryn, 2022). This dual nature of smartphone use—both beneficial and detrimental—highlights the importance of studying not just the amount of time spent on smartphones, but also the type, purpose, and context of usage.
Furthermore, much of the existing literature is based on studies from Western contexts, which may not fully capture the smartphone use patterns and educational challenges faced by students in the Philippines or other Southeast Asian countries. Cultural attitudes toward technology, education systems, socioeconomic factors, and digital literacy levels can all influence how smartphones are used and how they affect attention. Therefore, a localized study focusing on Filipino college students is crucial to generate context-specific insights and recommendations relevant to this demographic.
This study seeks to explore and clarify the relationship between smartphone usage and attention span in the context of the digital behaviors of college students. By identifying patterns, perceptions, and potential negative or positive correlations, the research aims to inform institutional policies, curriculum design, and digital wellness initiatives. Ultimately, the findings may help educators, psychologists, and policymakers develop strategies that harness the educational benefits of smartphones while minimizing their cognitive drawbacks.
While the intersection of technology and cognition has been a topic of interest for years, there remains a lack of consensus on how smartphone usage specifically affects attention span, especially among college students. Numerous studies have confirmed a general association between high screen time and attentional issues (Wilmer, Sherman, & Chein, 2022; Hadlington & Murphy, 2021), but many of these investigations fail to isolate smartphone usage from broader digital behaviors, such as general internet use or television consumption. Consequently, the precise cognitive impact of smartphones—given their unique interactive and immersive features—remains insufficiently explored.
Moreover, many prior studies emphasize quantitative metrics such as total screen time or number of device pickups, but neglect to consider the qualitative dimensions of smartphone use. This includes examining why students use smartphones (e.g., academic purposes vs. entertainment), when they use them (e.g., during lectures, before sleep), and how usage habits might moderate attention span. Recent findings suggest that the context and purpose of smartphone use are crucial variables that can either buffer or exacerbate its cognitive effects (Kates, Wu, & Coryn, 2022). However, few studies have integrated these behavioral nuances into their designs, resulting in a narrow understanding of smartphone-attention dynamics.
Another notable gap is the underrepresentation of longitudinal and causal research designs. Most studies to date are cross-sectional, capturing only a snapshot of behavior and cognition. While these studies can identify correlations, they do not reveal whether smartphone use causes reduced attention or whether individuals with lower baseline attention are more prone to excessive phone use (Jiang et al., 2021). Longitudinal or experimental studies could better clarify the directionality and strength of this relationship. However, such designs remain scarce, and existing data often lack ecological validity due to reliance on self-report measures rather than objective tracking tools.
Additionally, current literature tends to generalize findings across diverse populations without considering socio-cultural differences . In particular, there is a dearth of empirical research focusing on college students in Southeast Asia, including the Philippines, where digital behavior patterns, academic pressures, and socioeconomic contexts differ from those in Western countries. Cultural factors such as collectivism, family expectations, and community-based learning may influence how students engage with smartphones and manage their attention (Mei et al., 2023). The absence of culturally grounded research impedes the development of locally relevant guidelines for digital wellness and academic success.
Finally, many studies overlook individual difference variables such as time management skills, emotional regulation, academic motivation, and mental health status, all of which could mediate or moderate the impact of smartphone use on attention. For example, a student with strong executive functioning may be able to navigate multiple apps without significant cognitive impairment, while another may struggle to maintain focus during even brief periods of multitasking. Understanding these individual factors can lead to more tailored interventions, yet existing research rarely includes them in analytical models (Gazzaley & Rosen, 2022).
In light of these gaps, there is a compelling need for a focused, contextually relevant, and methodologically rigorous study that explores the relationship between smartphone usage and attention span among college students. This research will address both the quantitative and qualitative aspects of smartphone behavior, incorporate cultural and individual variables, and contribute new insights into how modern digital habits shape cognitive performance in the academic setting.
The purpose of this study is to examine the relationship between smartphone usage and attention span among college students in the digital era. Specifically, it aims to explore how the frequency, duration, and nature of smartphone use affect students' ability to sustain attention in academic contexts. As smartphone dependency becomes increasingly embedded in students’ daily routines, it is crucial to identify whether and how these digital behaviors contribute to cognitive challenges that may hinder learning and academic performance.
This study also seeks to distinguish between different types of smartphone use—academic, recreational, and social—to determine which usage patterns are more strongly associated with reduced or sustained attention span. By identifying these patterns, the research aims to clarify the potential cognitive consequences of multitasking, constant notifications, and app-switching behaviors commonly reported among students.
Furthermore, the study intends to generate culturally relevant insights by focusing on college students in the Philippines, an underrepresented demographic in the existing literature. It will take into account contextual factors such as cultural norms, academic pressures, and individual self-regulation strategies that may influence the relationship between smartphone use and attention span.
Ultimately, the findings of this study aim to inform educators, mental health professionals, policymakers, and students themselves about the impact of digital habits on cognitive functioning. By doing so, the research hopes to contribute to the development of interventions, awareness programs, and academic policies that promote healthier and more mindful technology use among college students in the digital age.
This study is grounded in two key psychological theories relevant to digital behavior and cognitive functioning in the modern era: The Limited Capacity Model of Mediated Message Processing (LC4MP) and Self-Regulation Theory. These contemporary psychological frameworks offer an in-depth understanding of how sustained smartphone use affects attention span, particularly among college students in an information-rich and distraction-heavy environment.
1. Limited Capacity Model of Mediated Message Processing (LC4MP)
The Limited Capacity Model (Lang, 2000) postulates that individuals have a finite amount of cognitive resources available for processing information. When media stimuli—such as social media feeds, notifications, videos, and text messages—compete for those resources, users must continuously allocate, store, and retrieve information under constrained cognitive load. With the omnipresence of smartphones in college students' lives, this competition for attention is intensified.
Recent extensions of LC4MP have confirmed that multitasking across mobile applications reduces working memory efficiency and impairs sustained attention. For example, Xu and David (2021) emphasized that frequent task-switching on smartphones leads to attentional fragmentation, where cognitive focus is repeatedly interrupted, making it difficult to complete tasks requiring continuous concentration. This model helps explain how modern smartphone use taxes cognitive resources and undermines attentional control in academic settings.
2. Self-Regulation Theory
Self-Regulation Theory (Baumeister & Heatherton, 1996) emphasizes an individual’s ability to control behaviors, emotions, and attention to achieve long-term goals. In the digital era, where smartphones provide immediate gratification and constant stimulation, self-regulation is often challenged. Individuals who struggle with digital self-control may find themselves repeatedly distracted, impulsively checking their phones during study or class, which depletes attentional resources over time.
Recent research has applied Self-Regulation Theory to digital behavior, showing that students with lower self-regulatory capacity report greater smartphone dependency and more difficulties focusing on academic tasks (Li, Lepp, & Barkley, 2021). This theory underscores the psychological mechanism by which internal control (or lack thereof) mediates the impact of external digital stimuli on attention.
3. Integration and Relevance to the Present Study
Together, LC4MP and Self-Regulation Theory provide a robust psychological foundation for examining how smartphones influence attention span. While LC4MP highlights the cognitive limitations in processing simultaneous digital inputs, Self-Regulation Theory accounts for behavioral and emotional factors that influence how students manage or fail to manage their digital habits. These frameworks are especially relevant for college students navigating high academic demands alongside constant digital connectivity.
By adopting these theories, this study aims to investigate not only the observable relationship between smartphone usage and attention span but also the underlying psychological mechanisms, such as cognitive overload and poor self-regulation, that contribute to this relationship in the digital age.
Conceptual Framework
This conceptual framework provides a structured lens to examine not just if smartphone use affects attention, but how and under what conditions. It emphasizes the cognitive and behavioral dimensions of digital device use and calls attention to individual psychological resources (like self-regulation) that can either buffer or amplify its effects.
Research Questions
1. What is the level of smartphone usage among college students in terms of frequency, duration, and purpose (e.g., academic, social, entertainment)?
2. What is the level of attention span among college students based on self-reported and/or observational measures?
3. Is there a significant relationship between the overall smartphone usage and the attention span of college students?
4. Do different types of smartphone use (academic, recreational, and social) have varying effects on students' attention span?
5. Are there significant differences in attention span based on the intensity of smartphone use (e.g., light, moderate, heavy users)?
Methodology
Research Design
This study employs a quantitative, correlational-comparative research design to investigate the relationship between smartphone usage and attention span among college students in the digital era. This approach is appropriate as it allows for the collection and statistical analysis of numerical data to identify patterns, relationships, and group differences. The design integrates descriptive, correlational, and comparative components to address the various research questions comprehensively.
The descriptive aspect of the study aims to determine the levels of smartphone usage in terms of frequency, duration, and purpose (academic, recreational, and social), as well as the self-reported and/or observed levels of attention span among college students. The correlational component investigates whether a statistically significant relationship exists between smartphone usage and attention span. Furthermore, the comparative dimension examines whether different types and intensities of smartphone usage are associated with varying levels of attention span.
The main variables in this study include smartphone usage as the independent variable and attention span as the dependent variable. Smartphone usage was assessed in three dimensions: frequency (how often students use their phones), duration (average daily usage in hours), and purpose (academic, social, and entertainment). Attention span will be evaluated using standardized self-report scales and, if feasible, observational data. To further analyze the impact of usage intensity, students were categorized into light, moderate, and heavy smartphone users based on composite scores, which will serve as the grouping variable for comparative analysis.
Participants
The participants of this study consisted of 150 college students enrolled in various state colleges and universities (SUCs) in Metro Manila during the Academic Year 2023–2024. These students were selected based on their regular use of smartphones, which served as a key criterion for inclusion in the study. The participants represented a diverse range of academic programs and year levels, ensuring that the findings would be generalizable across different student groups. Smartphone usage, being deeply integrated into students' daily lives for communication, academic engagement, and leisure activities, made this population highly relevant for examining the relationship between smartphone usage and attention span. A purposive sampling technique was used to target students who actively used smartphones. The sample size of 150 was considered sufficient for the statistical requirements of correlational and comparative analysis and was consistent with sample sizes used in similar behavioral and cognitive research.
To ensure representativeness, efforts were made to include students from a variety of courses such as liberal arts, sciences, engineering, and education. Gender distribution, academic year level, and academic load were also considered during selection to minimize sampling bias and to explore potential subgroup variations. Recruitment was conducted through coordination with student affairs offices, professors, and class group chats, where interested participants were briefed on the study and invited to participate voluntarily.
Before data collection, participants were asked to confirm their average daily smartphone usage through a short eligibility checklist to verify their alignment with the inclusion criteria. Only those who reported consistent smartphone use for both academic and non-academic purposes were included. Informed consent was obtained from all participants, and they were assured of confidentiality, anonymity, and the voluntary nature of their participation. Ethical approval was secured from the institutional review board, and all procedures were carried out in accordance with ethical standards for research involving human participants.
Sampling
The most appropriate sampling technique for this study was purposive sampling, a non-probability method wherein participants were selected based on specific characteristics that align with the objectives of the research. In this case, the key criterion was regular smartphone usage among college students, as the study aimed to examine how this behavior relates to attention span. Purposive sampling allowed the researcher to deliberately target individuals who were most relevant and informative for addressing the research questions.
This technique was ideal because it ensured that all participants actively used smartphones for academic, social, or recreational purposes—behaviors central to the conceptual framework. It also enabled the inclusion of a diverse set of respondents from various academic disciplines and year levels, which increased the representativeness and generalizability of the findings within the context of SUCs in Metro Manila.
To further enhance the sample’s diversity, a stratified purposive sampling approach was applied. In this method, the population was divided into relevant subgroups (e.g., course/program, year level, gender), and participants were purposively selected from each stratum. This helped ensure that key demographic categories were proportionally represented, reducing bias and allowing for subgroup analysis (e.g., comparing smartphone use patterns between freshmen and seniors).
The study aimed to compare attention span across levels of smartphone use intensity (light, moderate, heavy users), quota sampling could also be useful. In this case, a target number of participants per category would be identified in advance to ensure balanced representation across smartphone usage levels. However, purposive sampling remains the primary and most suitable technique due to its alignment with the study’s exploratory and criterion-based goals.
Data Gathering Procedure
The data collection for this study was conducted during the second semester of the Academic Year 2023–2024. Prior to the actual data gathering, ethical approval was secured from the institutional review board, and permission was obtained from the administrators of selected state colleges and universities in Metro Manila. Coordination with faculty members and student affairs offices facilitated access to student participants from various academic programs and year levels.
Participants were recruited using a purposive sampling technique. Interested students were approached through class announcements, online messaging platforms (such as group chats and university learning portals), and coordination with instructors. A brief screening checklist was provided to determine if potential participants met the inclusion criteria—specifically, regular smartphone usage for academic, social, and recreational purposes. Those who qualified were invited to participate and were given an informed consent form that outlined the study’s purpose, procedures, voluntary nature, and confidentiality measures.
Once consent was obtained, participants were asked to complete two standardized instruments via an online survey form distributed through Google Forms. The first instrument was the Smartphone Usage Questionnaire, which measured the frequency, duration, and purpose of smartphone use. The second instrument was the Mindful Attention Awareness Scale (MAAS), a validated self-report measure used to assess attention span. Both instruments were pilot-tested on a small group of students prior to formal data collection to ensure clarity and reliability within the context of the local academic environment.
Participants were given ample time to complete the questionnaires, and reminders were sent to ensure high response rates. The survey responses were automatically recorded in a secure, password-protected database. To ensure anonymity, personal identifiers were not collected, and each response was assigned a unique code. After data collection, responses were screened for completeness and accuracy before proceeding to the data analysis phase.
Throughout the process, all ethical guidelines for research involving human participants were strictly followed. Participation was voluntary, and respondents were informed that they could withdraw from the study at any point without any negative consequences
instrumentation
To measure the attention span of college students in this study, the Mindful Attention Awareness Scale (MAAS) is a 15-item scale developed by Brown and Ryan (2003) was employed. The MAAS is a widely validated self-report instrument designed to assess individual differences in attention and awareness of the present moment in daily life. While it is not an attention span test in the narrowest cognitive sense (like those used in neuropsychological assessments), it captures a relevant construct of attentional control and mindfulness, which correlates strongly with the ability to maintain focus—especially in educational settings (Bajaj et al., 2021).
The MAAS consists of 15 items, each rated on a 6-point Likert scale ranging from 1 (almost always) to 6 (almost never). Higher scores reflect greater levels of mindful attention and awareness, which are indicative of a longer and more sustained attention span. Sample items include: “I find myself doing things without paying attention,” and “I rush through activities without being really attentive to them.”
Numerous studies have confirmed the construct validity and internal consistency of the MAAS in diverse populations, including college students. A recent validation study by Medvedev et al. (2021) reaffirmed that the MAAS is a unidimensional and psychometrically robust instrument, with excellent i nternal consistency reliability (Cronbach’s alpha ranging from 0.85 to 0.92 across samples).
In a Philippine context, local studies have also supported the reliability of the MAAS. For example, Dizon et al. (2022) reported a Cronbach’s alpha of 0.87 among Filipino undergraduate students, suggesting strong reliability in local academic environments. Moreover, confirmatory factor analysis (CFA) results in both international and local studies have consistently indicated a good model fit, supporting the scale’s content and factorial validity (Sahdra et al., 2020).
For the purpose of this study, participants’ total MAAS scores were computed by averaging their responses across the 15 items. The scores were then categorized into three levels of attention span, as follows: 1. Low Attention Span: Scores ranging from 1.00 to 2.99; 2. Moderate Attention Span: Scores ranging from 3.00 to 4.49 and 3. High Attention Span: Scores ranging from 4.50 to 6.00
These cutoffs are consistent with categorizations used in related mindfulness-attention studies (e.g., Black et al., 2020; Bajaj et al., 2021), which typically segment mindfulness or attentional scores into tertiles or based on normative distribution.
This categorization allowed for a more nuanced analysis of how different intensities and types of smartphone use impacted students across various attention span levels. By using a validated and reliable instrument like the MAAS, this study ensured the credibility and replicability of its findings in assessing students’ attentional functioning.
Ethical Considerations
This study strictly adhered to ethical standards in the conduct of research involving human participants. Prior to the data collection, the research proposal underwent a thorough review and was granted approval by the Institutional Review Board (IRB) of the researcher’s academic institution. This ensured that the study complied with established ethical principles such as respect for persons, beneficence, and justice, as outlined in national and international ethical guidelines.
One of the foremost ethical considerations was obtaining informed consent from all participants. Before participating in the study, students were provided with a digital informed consent form explaining the purpose of the research, the procedures involved, their expected participation, and the voluntary nature of their involvement. It was emphasized that participants had the right to decline or withdraw from the study at any point without facing any penalties or academic consequences. Only those who provided their consent were allowed to proceed with the survey.
To protect the confidentiality and anonymity of the participants, no personally identifiable information was collected in the survey forms. Each participant’s response was recorded using a unique code to ensure privacy. All data collected were stored in a secure, password-protected digital platform accessible only to the researcher. The data were used solely for the purpose of academic research and were not disclosed to any unauthorized third parties.
Additionally, the researcher ensured that there was minimal to no risk to participants. The study did not involve any physical procedures or intrusive psychological assessments. All questions in the survey were structured in a way that was respectful, non-invasive, and appropriate for the target population. Participants were also provided with contact information in case they had questions or concerns about the study.
Lastly, the ethical conduct of the study was maintained throughout the entire research process—from recruitment to data collection, analysis, and dissemination of results. The findings of the study will be reported objectively and without bias, and participants will remain unidentifiable in all publications and presentations.
Data Analysis
The data collected from the 150 college student participants were analyzed using quantitative statistical techniques to address the research questions and test the hypothesized relationships between smartphone usage and attention span. Prior to formal analysis, the dataset was screened for completeness, and incomplete or invalid responses were excluded to ensure data accuracy and integrity.
Descriptive statistics were first computed to summarize the demographic characteristics of the participants, as well as their levels of smartphone usage and attention span. Measures such as mean, standard deviation, frequency, and percentage were used to describe the frequency, duration, and purpose of smartphone use (academic, social, and entertainment), as well as attention span scores based on the standardized instrument.
To examine the relationship between overall smartphone usage and attention span, a Pearson Product-Moment Correlation analysis was conducted. This allowed the researcher to determine the strength and direction of the relationship between the two variables. A significance level (alpha) of 0.05 was used as the threshold for determining statistical significance.
To analyze whether different types of smartphone usage (academic, recreational, and social) had varying effects on attention span, a multiple regression analysis was performed. This approach identified which dimensions of smartphone use significantly predicted attention span levels while controlling for the influence of other types of use. The assumptions of normality, linearity, and multicollinearity were checked to ensure the validity of the regression model.
Additionally, to investigate whether attention span differed significantly across different levels of smartphone use intensity (light, moderate, and heavy users), a one-way Analysis of Variance (ANOVA) was conducted. Post hoc tests, such as the Tukey Honestly Significant Difference (HSD) test, were used to identify specific group differences when significant variance was found.
All statistical analyses were carried out using SPSS (Statistical Package for the Social Sciences). The findings were presented in tables and figures to facilitate interpretation and support conclusions aligned with the study’s objectives. Results were interpreted carefully, with attention to both statistical significance and practical implications in the context of college students’ academic functioning and digital behavior.
RESULTS AND DISCUSSION
Table 1 Level of Smartphone Usage Among College Students (n = 150)
Illustrations are not included in the reading sample
Table 1 presents the level of smartphone usage among 150 college students in Metro Manila based on frequency, daily duration, and primary purpose. The results revealed that 51.3% of respondents reported using their smartphones daily, while 26% used them frequently (5–6 days per week). These findings align with the growing body of literature indicating that smartphone use among college students has become a daily and habitual behavior, particularly in digital learning environments (Luqman et al., 2021; Yang et al., 2022).
In terms of duration, 35.3% of students reported spending 5–6 hours per day on their smartphones, and 32.7% used them for more than 6 hours daily, supporting studies that show excessive smartphone engagement is a common pattern among students navigating online academic and social demands (Yeh et al., 2022). This prolonged usage reflects how smartphones have become deeply embedded in student life, especially during and after the pandemic when remote learning and digital communication surged (Aboelmaged, 2021).
Regarding the purpose of smartphone use, the majority (40%) reported using smartphones primarily for social interactions (e.g., messaging, social media), followed by entertainment purposes (34.7%), such as gaming or streaming, and academic purposes (25.3%). This distribution reflects the dominance of non-academic smartphone use, a concern frequently cited in recent literature about attention f ragmentation and digital distraction (Busch & McCarthy, 2021; Jeong et al., 2023). Although smartphones serve as tools for learning, their primary use for social and entertainment activities may impact students’ attention spans and cognitive focus (Sha et al., 2020).
This data underscore the high frequency and intensity of smartphone use among college students, with a clear tilt toward non-academic engagement. These findings provide an important foundation for examining how such usage patterns may influence students’ attentional capacities, a concern highlighted by several scholars who suggest that the multifunctionality of smartphones can compromise sustained attention and task efficiency (Hadlington & Scase, 2022; Mohammadi et al., 2021).
Table 2 Level of Attention Span Among College Students (n = 150)
Illustrations are not included in the reading sample
Table 2 shows the distribution of attention span levels among 150 college students in Metro Manila, as measured through a self-report scale. The results indicate that a majority of the participants (48%) fell under the "moderate" attention span category, suggesting that while these students possess some ability to maintain focus on tasks, they may still experience occasional lapses in attention. This is consistent with the findings of Hadlington and Scase (2022), who noted that students in digital learning environments frequently oscillate between focus and distraction due to the competing demands of academic tasks and digital stimuli.
Notably, 32.7% of respondents exhibited low levels of attention span, pointing to significant challenges in maintaining sustained cognitive engagement. This outcome is concerning, as low attention span has been associated with reduced academic performance, increased task-switching behavior, and higher susceptibility to digital distractions (Busch & McCarthy, 2021; Jeong et al., 2023). The prevalence of low attention span in nearly one-third of the sample supports the growing concern that overexposure to digital media, particularly via smartphones, may impair attentional control mechanisms (Sha et al., 2020).
On the other hand, only 19.3% of students demonstrated a high level of attention span, which implies that a relatively small segment of the student population maintains strong focus and attentional regulation. These students are likely to be more resistant to digital distractions and may possess better self-regulatory skills, a pattern supported by recent cognitive research on mindfulness and executive functioning (Yeh et al., 2022). This small percentage reinforces the notion that sustained attention is becoming increasingly rare in a hyper-connected digital era, particularly among younger populations heavily reliant on smartphones for both academic and non-academic purposes (Luqman et al., 2021).
These findings illustrate a potentially problematic trend among college students, where only a minority exhibit high attentional control, while a substantial number operate in a moderate-to-low attention span range. This trend underscores the need for interventions focused on digital wellness, mindfulness training, and cognitive self-regulation to help students manage their smartphone use and enhance attentional capacities (Mohammadi et al., 2021; Yang et al., 2022).
Table 3 Correlation Between Smartphone Usage and Attention Span (n = 150)
Illustrations are not included in the reading sample
Note: r = Pearson correlation coefficient; p < 0.01 (2-tailed)
Table 3 presents the results of a Pearson correlation analysis examining the relationship between smartphone usage and attention span among 150 college students in Metro Manila. The findings revealed a moderate, negative, and statistically significant correlation (r = -0.421, p < 0.01), indicating that as smartphone usage increases, attention span significantly decreases. This relationship suggests that students who frequently and intensively use smartphones are more likely to experience challenges in maintaining cognitive focus and sustained attention.
These results are consistent with several recent studies emphasizing the adverse cognitive effects of excessive smartphone use. According to Hadlington and Scase (2022), continuous engagement with smartphones, particularly in multitasking contexts, disrupts executive functioning and impairs sustained attention. Likewise, Mohammadi et al. (2021) found that heavy smartphone use among university students was significantly associated with reduced attentional control and greater task-switching tendencies. The moderate negative correlation in this study mirrors such findings, providing additional empirical support that overuse of digital devices—especially for non-academic purposes—can erode the ability to concentrate effectively.
Moreover, Jeong et al. (2023) argue that the omnipresence of smartphones in students’ academic and personal lives contributes to frequent attentional shifts, especially when students are exposed to multiple applications such as social media, messaging, and gaming. These digital interruptions can fragment attention and reduce students’ ability to engage deeply in academic tasks. The findings from Table 3 affirm this concern and suggest the need for behavioral interventions to promote more mindful smartphone usage habits.
Additionally, the significant relationship identified in this study supports the conceptual view that technological overstimulation in the digital age may have long-term implications for cognitive performance among young adults (Sha et al., 2020). This highlights the importance of incorporating digital well-being and self-regulation training within college wellness programs to mitigate the cognitive costs of heavy smartphone engagement.
Table 4 ANOVA Results: Effects of Different Types of Smartphone Use on Attention Span (n = 150)
Illustrations are not included in the reading sample
Note: p < 0.01 (significant at 1% level)
Table 4 presents the results of a one-way ANOVA conducted to examine whether different primary types of smartphone use—academic, recreational, and social—have varying effects on college students' attention span. The analysis revealed a statistically significant difference in attention span scores across the three groups (F = 7.68, p = 0.001), indicating that the nature of smartphone usage has a meaningful impact on students’ ability to maintain attention.+
Among the groups, students who primarily used smartphones for academic purposes recorded the highest mean attention span score (M = 3.47, SD = 0.65). This finding suggests that purposeful and goal-oriented smartphone activities, such as accessing educational resources, note-taking, or participating in virtual classes, may support or even enhance attentional regulation. This aligns with the findings of Yeh, Lin, and Lin (2022), who reported that structured academic smartphone use can facilitate cognitive engagement and promote sustained focus when integrated meaningfully into students' learning routines.
In contrast, students who predominantly used their smartphones for recreational activities (e.g., gaming, streaming, browsing) had a lower mean attention span (M = 2.88, SD = 0.72), while those who primarily used their smartphones for social interactions (e.g., social media, messaging) had the lowest attention span scores (M = 2.65, SD = 0.81 ). This supports recent research indicating that frequent use of social media platforms fosters fragmented attention and habitual task-switching, ultimately impairing cognitive persistence (Hadlington & Scase, 2022; Yang et al., 2022). Moreover, Mohammadi et al. (2021) highlight that social smartphone use is associated with increased distractions, leading to reduced academic productivity and impaired executive functioning.
These findings underscore the importance of distinguishing between types of smartphone use, rather than viewing screen time as a monolithic measure. While smartphone use in itself is not inherently harmful, the purpose and context of use significantly shape its cognitive consequences. As Sha et al. (2020) noted, the passive and emotionally driven nature of social media engagement can diminish attention span more severely than structured academic or goal-directed use.
The data from Table 4 suggest that while academic smartphone use may coexist with or support attentional control, recreational and especially social uses may undermine students' cognitive focus. These insights have important implications for digital literacy education and interventions that aim to promote intentional and balanced smartphone usage among college students in the digital age.
Table 5 One-Way ANOVA: Differences in Attention Span Based on Smartphone Use Intensity (n = 150)
Illustrations are not included in the reading sample
Illustrations are not included in the reading sample
Note: p < 0.01 = significant at the 1% level
Table 5 shows the results of a one-way ANOVA conducted to determine whether intensity of smartphone use (categorized as light, moderate, or heavy) is associated with significant differences in attention span among college students. The analysis revealed a statistically significant difference in attention span scores among the three groups (F = 9.91, p < 0.01), suggesting that the amount of time spent using smartphones plays a key role in students’ attentional capacity.
Students classified as light users (e.g., using smartphones less than 3 hours per day) had the highest mean attention span score (M = 3.58, SD = 0.61), followed by moderate users (3–6 hours/day; M = 3.01, SD = 0.70), while heavy users (6+ hours/day) had the lowest attention span (M = 2.52, SD = 0.85). These results support the growing body of literature that links increased screen time with reduced cognitive control. For instance, Hadlington and Scase (2022) found that excessive smartphone engagement negatively affects sustained attention and increases susceptibility to distraction. Similarly, Mohammadi et al. (2021) observed a significant inverse relationship between daily smartphone use and attentional performance in university populations.
The findings also align with the cognitive load theory, which posits that heavy smartphone use imposes frequent interruptions that deplete attentional resources and overload working memory (Jeong et al., 2023). As heavy users engage in constant multitasking across multiple apps and social media platforms, their ability to maintain prolonged attention to academic tasks diminishes. In contrast, light users may benefit from lower cognitive demands and reduced exposure to digital distractions.
These outcomes underscore the importance of monitoring smartphone usage among students, not only in terms of content but also usage volume. Educational institutions and mental health professionals should consider implementing digital hygiene programs to raise awareness about balanced usage patterns and their implications for cognitive performance (Yeh et al., 2022). Ultimately, reducing heavy smartphone dependence could serve as a preventive strategy to maintain or improve attentional capacity in the academic context.
Summary
This study explored the relationship between smartphone usage and attention span among 150 college students enrolled in various state colleges and universities in Metro Manila during the Academic Year 2023–2024. The participants were categorized by their frequency, duration, purpose, and intensity of smartphone use. The findings from Table 1 showed that the majority of students used smartphones frequently and for extended durations, particularly for social and recreational purposes, with academic use being the least frequent. Table 2 revealed that the overall level of attention span among the participants was moderate, with variability depending on individual usage habits.
The correlational results in Table 3 indicated a significant negative relationship between total smartphone usage and attention span, implying that increased smartphone use is associated with lower levels of attentional control. Meanwhile, Table 4 demonstrated that the purpose of smartphone use significantly affected attention span, with academic users showing higher attention spans than recreational or social users. These findings collectively suggest that while smartphones are ubiquitous and multifunctional, their effects on cognitive functions like attention are complex and dependent on how and how much they are used.
Future Directions
Future research should adopt a longitudinal approach to better understand the causal relationships between smartphone use and attention span. While the present study identified significant associations and group differences, the cross-sectional design limits conclusions about directionality or long-term effects. Longitudinal data could reveal whether sustained heavy smartphone use leads to lasting cognitive impacts or whether changes in attention are reversible with behavioral modification. Moreover, future studies should incorporate additional psychological constructs such as self-regulation , mindfulness, executive function, and emotional well-being to explore their potential moderating or mediating roles (Li et al., 2021; Sahdra et al., 2020). Including diverse samples across age groups, academic disciplines, and geographic locations would also enhance generalizability. Furthermore, employing objective tools like digital tracking apps and neurocognitive assessments can complement self-report measures and provide a more nuanced understanding of attentional shifts due to smartphone exposure (Wilmer et al., 2022; Hadlington & Murphy, 2021). Finally, future studies may explore the effectiveness of intervention strategies—such as digital detox programs or mindfulness-based cognitive training—to mitigate the adverse effects of problematic smartphone use on student attention and academic performance.
Conclusion
The findings of this study underscore the significant cognitive implications of smartphone usage among college students. Specifically, increased intensity and socially driven smartphone use are linked to lower attention spans, while academic-oriented smartphone activities appear to mitigate this effect. These results contribute to the growing literature on digital behavior and cognitive psychology, particularly in the context of higher education during the digital era. As smartphones continue to be indispensable tools for learning and social interaction, understanding their nuanced impact on attention is crucial for promoting effective learning environments and healthy digital habits among students.
Recommendations
Based on the findings, it is recommended that higher education institutions develop structured programs promoting mindful and purposeful smartphone use. Administrators and faculty members should consider integrating digital literacy and time-management workshops into student development programs to cultivate awareness of the cognitive costs of excessive smartphone engagement. Additionally, educators can design technology-integrated teaching strategies that leverage academic smartphone use while minimizing distraction. Counseling and wellness offices are encouraged to offer mindfulness training and attention-enhancement workshops, as mindfulness practices have been found to improve attentional control and reduce mind-wandering It is also recommended that policymakers explore the formulation of guidelines that balance digital integration in education with students' cognitive and psychological well-being. Finally, students themselves should be empowered through awareness campaigns and peer support programs to develop self-monitoring habits, set screen-time boundaries, and prioritize tasks that foster sustained attention and academic success.
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The Mindful Attention Awareness Scale (MAAS)
The trait MAAS is a 15-item scale designed to assess a core characteristic of mindfulness, namely, a receptive state of mind in which attention, informed by a sensitive awareness of what is occurring in the present, simply observes what is taking place.
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Instructions: Below is a collection of statements about your everyday experience. Using the 1-6 scale below, please indicate how frequently or infrequently you currently have each experience. Please answer according to what really reflects your experience rather than what you think your experience should be. Please treat each item separately from every other item.
Illustrations are not included in the reading sample
1. I could be experiencing some emotion and not be conscious of it until sometime later.
2. I break or spill things because of carelessness, not paying attention, or thinking of something else.
3. I find it difficult to stay focused on what’s happening in the present.
4. I tend to walk quickly to get where I’m going without paying attention to what I experience along the way.
5. I tend not to notice feelings of physical tension or discomfort until they really grab my attention.
6. I forget a person’s name almost as soon as I’ve been told it for the first time.
7. It seems I am “running on automatic,” without much awareness of what I’m doing.
8. I rush through activities without being really attentive to them.
9. I get so focused on the goal I want to achieve that I lose touch with what I’m doing right now to get there.
10. I do jobs or tasks automatically, without being aware of what I'm doing.
11. I find myself listening to someone with one ear, doing something else at the same time.
12. I drive places on ‘automatic pilot’ and then wonder why I went there.
13. I find myself preoccupied with the future or the past.
14. I find myself doing things without paying attention.
15. I snack without being aware that I’m eating.
Scoring: To score the scale, simply compute a mean (average) of the 15 items.
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- PhD, RPsy, LPT, CHRA Josephine Manapsal (Author), 2024, Exploring the Relationship Between Smartphone Usage and Attention Span Among College Students in the Digital Era, Munich, GRIN Verlag, https://www.grin.com/document/1593867
