Undergraduate students’ perception of smartphone addiction and its impact on themselves and their academic performance: a case study

Abstract

The main objective of the present study was to investigate undergraduate students’ perception of smartphone addiction and its impact on themselves and their academic performance in Takhar province. 1321 participants from Takhar University and 4 private universities responded to an online survey questionnaire. The researchers used SPSS Version 26.0 to analyze the data. The findings revealed that undergraduate students were highly addicted to smartphones, and the excessive use of smartphones had an adverse effect on the academic performance of students. The results showed that there were statistically significant differences in smartphone addiction by the respondents’ gender, access to social media and daily hours of smartphone usage. Moreover, a strong negative correlation was found between smartphone addiction and its impact on students’ academic performance. The findings of the study are crucial to higher education leaders because they may help them develop policies to reduce the excessive and inappropriate use of smartphones in classrooms.

Keywords:

• Use of technology
• impact of smartphone addiction
• academic performance
• higher education of Afghanistan

REVIEWING EDITOR:

• Maria Popescu, Strategic Communication, Carol I National Defense University, Romania

SUBJECTS:

• Psychological Science
• General Psychology
• Multidisciplinary Psychology
• Psychology of New Media
• Techniques & Interventions - Psychosocial & Behavioural Issues
• Exercise Psychology
• Psychoanalysis - Performance Tests
• Media Psychology

1. Introduction

Technology has transformed the way in which people live and communicate in the twenty first century (Hashemi et al., 2022). A smartphone is a type of modern technology, which is usually used for communication and other different purposes (Shakoor et al., 2021). The use of smartphones has increasingly changed the lives of people in recent decades throughout the world (Arefin et al., 2017; Hashemi, 2021c). Boumosleh and Jaalouk (2018) believed that smartphones have simplified the life of human being and these devices have played an important role in enhancing knowledge and daily communications.

Although Afghanistan has experienced decades of conflicts and instabilities and remained an underdeveloped country in the world (Hashemi, 2021a; Noori, 2021; Noori et al., 2020; Orfan et al., 2022), the number of smartphone users has dramatically grown in the country. According to World Bank (2019), the number of mobile phone users was around 20.92 million, and the number of social media users were about 3.60 million. A report by Abdullah (2021) showed that there were around 7.65 million active Internet users in Afghanistan in 2020, which indicates a significant increase in the number of both mobile and Internet users in the last decade in Afghanistan.

Smartphones were ostensibly introduced to reduce the functions of cameras, video recorders, digital watches, and other devices. For example, the purchase of digital cameras was extremely decreased among the young generation, and a huge number of them use their smartphone’s cameras to take films and photos (Darko-Adjei, 2019). According to Darko-Adjei (2019), having a smartphone is similar to having a small device in your pocket. A smartphone’s utility is not limited to making and receiving phone calls. Typical features include browsing, checking health status, sending and receiving emails, watching videos, listening to music, chatting, sharing photos, videos, and other documents. It is no surprise that the smartphone has resulted in an exponential increase in social media usage (Al-Fawareh & Jusoh, 2017). Therefore, people are so dependent on smartphones and cannot live without them particularly students who have been addicted, which affects their academic performance and health (Raza et al., 2020).

In Afghanistan, the misuse and addiction of smartphone is becoming more of a concern because many students have gotten used to mobile applications. As faculty members, we are aware of the university students’ fascination with smartphones, and the growing prevalence of harmful consequences of the excessive use of smartphones in their daily life. Thus, the overuse of smartphones by students has caused a lack of interest in reading course materials and reluctance in taking part in the class activities and projects.

1.1. Research question

1. To what extent are undergraduate students addicted to smartphone?

2. To what extent does the use of smartphone affect students’ academic performance?

3. Are there statistically significant differences in smartphone addiction by the respondents’ gender, daily hours of smartphone usage and access to social media?

4. Is there any relationship between students’ smartphone addiction and their academic performance?

2. Literature review

A smartphone is defined as a portable device combining computing functions and mobile telephone into a well-designed unit, which facilitates web browsing, multimedia purposes and phone functions. A smartphone is typically a cell phone that accomplishes various functions along with a touchscreen interface, and an operating system that involves internet access for running and downloading applications (Boumosleh & Jaalouk, 2018; Hashemi & Kew, 2021). Smartphones are used by people in different contexts including business, education and communications, which are integral part of our everyday modern life and communication.

Smartphones serve different significant functions. They play an important role in critical aspect of learning, research and digital literacy, which support the learning process (Terras & Ramsay, 2016). Smartphones have been used for years and are generally becoming a compelling learning device to enhance teaching and learning activities in the online learning environments (Cochrane & Bateman, 2010). The use of smartphones is also advantageous to interact digitally, access lectures and online learning materials (Sari & Oktaviani, 2021). In the meantime, excessive use of smartphones causes addiction problems to the learners that negatively affect their learning outcome and academic achievement (Lee et al., 2015).

A large number of studies have investigated the impacts of smartphone addiction on students’ academic performance (Abbasi et al., 2021; Ahmed et al.2020; Aman et al., 2015; Bağcı & Pekşen, 2018; Fabito et al., 2018; Hong et al., 2012; Ifeanyi & Chukwuere, 2018; Kaur et al., 2018; Kibona & Rugina, 2015; Lau, 2017; Lepp et al., 2014; Nayak, 2018; Samaha & Hawi, 2016). A study carried out by Ifeanyi and Chukwuere (2018) exploring the impact of smartphone addiction on undergraduate students’ academic performance in South Africa and found that excessive use of smartphones significantly decreased students GPAs. Similarly, Abbasi et al. (2021) found that smartphone addiction was one of the main factors in reducing students’ academic performance. They further indicated that policymakers and parents would benefit from understanding the value of improving and encouraging physical activity in young people by looking at physical activity as a prevention factor in decreasing the use of a smartphone. On the contrary, a study conducted by Boumosleh Matar and Jaalouk (2017) figured out that smartphone addiction did not affect the GPA or academic performance of students.

In the same vein, Bağcı and Pekşen (2018) investigated the smartphone addiction of vocational students and found that smartphone addiction could impact different dimensions of life. Smartphone users with a high percentage of usage, tend to be more addicted to smartphone than those who use it less frequently. Their findings also indicated that those with access to social media were more addicted to the smartphone than those without access. Moreover, Hong et al. (2012) identified the reasons why people specifically overused smartphones. They related smartphone addiction to the individual’s inner psychological features and believed that university students with addiction habits were highly affected in terms of their performance. Similarly, Ifeanyi and Chukwuere (2018) believed that smartphone addiction could lead to distraction and reduce students’ learning capabilities. On the other hand, Kaur et al. (2018) explored both the positive and negative impacts of smartphone and reviewed 18 research papers by categorizing their findings into positive and negative impact of smartphone and reported that only three studies examined the positive effects of smartphone usage and the fifteen other studies focused on the negative effects of smartphone usage. They reported that smartphone was of positive impact when students used it to access learning materials, but it was of negative effect when they used it excessively, which led to their addiction.

Sachitra (2015) studied the Internet addiction and academic performance among university students. He explored the relationship between academic performance and Internet addiction. His findings revealed that there was a negative relationship between Internet addiction and academic performance. The study also found that there was a significant difference in Internet addiction according to gender. Likewise, Sabbah et al.(2019) investigated the risk of smartphones addiction between males and females. The findings showed that male students had a higher risk of smartphone addiction compared to female students. In another context, Xu (2017) studied the relationship between smartphone addiction and social anxiety. He believed that people who used their phones excessively suffered from serious social and psychological consequences. The contact patterns of students, who have become increasingly reliant on smartphones, are steadily changing because of the rapid social rhythm, everyday busy life, and complex interpersonal relationships. He further suggested that in order to prevent students’ excessive use of smartphones, teachers should assign some certain limitations to reduce smartphone usage.

Another study was carried out by Ma et al. (2020) investigating the effects of smartphone addiction on students learning process and found that smartphone addiction positively affected the learning process of undergraduate students. However, cognitive failure is the crucial factor also known of the affected tool for phone addiction. Similarly, Alhassan et al. (2018) holding a cross-sectional research study found out the relationship between smartphone addiction and depression. Surprisingly, their findings also showed that those who were at the university had higher level of addiction to smartphone than those who were at the school. Equally, a study conducted by Luk et al. (2018) came to similar conclusions; students in the higher-level of education had a higher level of smartphone addiction than those of the lower level of education. Therefore, smartphone addiction to the higher education level remains problematic and requires more endeavors to deal with.

Academic performance refers to how well students have met their short and long-term educational objectives, which are typically assessed using self-reported GPA. Studies indicate that the excessive use of smartphones negatively affects students’ academic achievement. For example, the research by Cao et al. (2018a) has looked into the multiple negative effects of smartphone and social networking sites whose excessive use significantly decreased students’ GPA and learning outcome. Only a few experiments in the field of information systems analysis have shown that psychological discomfort causes low academic performance and attendance, and it contributes to poor outcomes. In this regard, many studies have measured the academic performance of students according to their level of smartphone addiction (Arefin et al., 2017; Khan et al., 2019; Boumosleh & Jaalouk, 2018; Kibona & Magay, 2015; Mukhdoomi et al., 2020; Nayak, 2018).

Given the rapid rise in the usage of smartphone among university students, unfortunately, until now, little is known about students’ smartphone addiction and its impact on their academic performance in war-affected countries, and no study was found in the context of Afghanistan. Therefore, this study aims to fill the gap by investigating students’ perception of smartphone addiction and its impact on themselves and their academic performance. This study is crucial because it determines the consequences of smartphone addiction for students particularly at the university level since some of the previous studies found higher level of smartphone addiction among university students than the school students (Bağcı & Pekşen, 2018; Alhassan et al., 2018; Luk et al., 2018). The findings will be of significance for higher education stakeholders in particularly lecturers, institutions and the Ministry of Higher Education (the major managing and policymaking entity). They will help them develop policies at various levels (e.g. classroom and institution) to reduce the excessive use of smartphone among students and help them boost their academic achievement.

2.1. Conceptual framework

A number of empirical studies support the use of smartphone in the twenty first century. Among the theories, Venkatesh and Davis (2000) Technology Acceptance Model explained the perceived use of technology, its cognitive process of instrumental and social influence. This theory aimed to provide a foundation in improving understanding of user behavior. It describes how technology devices and smartphone addiction function. Smartphone addiction, like all other acquired behavior, can be changed (Aljomaa et al., 2016). Smartphone addiction is viewed as a product of a society’s history, according to a socio-cultural pattern. Finally, an integrative viewpoint holds that smartphone addiction is caused by a combination of personal, cultural, technological, environmental, and emotional influences. Therefore, smartphone addiction has been linked to the emergence of a variety of behavioral and mental disorders (Figure 1).

Figure 1. Conceptual Framework of the Study (Venkatesh & Davis, 2000).

3. Method

The present study employed a quantitative design in which a survey questionnaire was adapted to investigate the impact of smartphone addiction on Afghan students’ academic performance. Descriptive and inferential statistical analyses were utilized to analyze the data. The descriptive statistics were used to determine frequency, percentage, mean, and standard deviation of data. Inferential statistical tests were employed to examine whether there were statistically significant differences in smartphone addiction by the respondents’ gender, daily hours of smartphone usage and access to social media.

3.1. Participants

The participants of the study were both from public and private universities including males and females. There were 1321 respondents who completed the online questionnaire. Most of the participants (70%) were male and 30% of them were female. They were majoring in various fields at Takhar University (public university) and four private universities (Farjristan, Khana-e Danish, Payman and Rah-e Saadat). The respondents were between 18 and 30 years old at the time of the study (See Table 1).

Table 1. Respondents’ demographic profile.

Main variables	Sub-variables	Frequency	Valid percent
Gender	Male	926	70%
	Female	395	30%
Total		1321	100%
Age	18–25	872	66%
	25–30	297	22%
	above 30	152	12%
Total		1321	100%

3.2. Instrument

The researchers carried out a literature review to design the survey questionnaire. The questionnaire consisted of three parts. The first part with 4 items sought the demographic profile of the participants. The second part with 10 items, a validated smartphone addiction scale-short version (SAS-SV) originally developed by Kwon (2013), aimed to investigate students’ perceptions of smartphone addiction on a five-points Likert scale ranging from 1 strongly disagree to 5 strongly agree. The third part with 10 items, adapted from the work of Mukhdoomi et al. (2020), focused on students’ perceptions of impact of smartphone addiction on the their academic performance. For its application, the questionnaire was translated into Dari language (the lingua franca of Afghanistan) since English is a foreign language in the country (Orfan et al., 2021).

3.3. Validity

The questionnaire was presented to five research experts with competence in psychology, psychological counseling, measurement, and assessment to read and suggest improvement comments. They provided valuable and helpful suggestions on the clarity of each item. Some items were reworded, and revised according to the feedback received from them. To verify the construct validity of the measuring item, unidimensionality test through Rasch measurement model was applied. The unidimensionality test aims to identify whether the items in the survey fall into one common factor or measuring the same construct (Fisher, 2007). Variance explained by measure value greater than 40% is said to be sufficient to indicate the items are unidimensional. As shown in Tables 2 and 3, the variance explained by measure for the items measuring smartphone addiction and impact of smartphone Addiction on academic performance were 71.8% (very good), and 92.2% (excellent) respectively (Fisher, 2007). In addition, the unexplained variance in 1^st contrast for both surveys is <15% (Smartphone Addiction = 11.6%; impact of smartphone addiction on academic performance = 6.7%). The degree of the items measuring second dimension is low and acceptable.

Table 2. Unidimensionality for Smartphone Addiction Scale (n = 40).

Cronbach alpha (KR-20) Person raw score ‘Test’ Reliability = 0.87
Table of Standardized Residual variance (in Eigenvalue units)
– Empirical – Modeled
Total raw variance in observations =	35.5	100.0%	100.0%
Raw variance explained by measures =	25.5	71.8%	67.6%
Raw variance explained by persons =	7.3	20.7%	19.5%
Raw Variance explained by items =	18.1	51.1%	48.1%
Raw unexplained variance (total) =	10.0	28.2%	32.4%
Unexplained variance in 1st contrast =	4.1	11.6%	41.1%

Table 3. Unidimensionality for impact of smartphone addiction Scale (n = 40).

Cronbach alpha (KR-20) Person raw score ‘Test’ Reliability = 0.94
Table of Standardized Residual variance (in Eigenvalue units)
– Empirical – Modeled
Total raw variance in observations =	511.9	100.0%	100.0%
Raw variance explained by measures =	471.9	92.2%	85.5%
Raw variance explained by persons =	232.0	45.3%	42.0%
Raw Variance explained by items =	239.9	46.9%	43.5%
Raw unexplained variance (total) =	40.0	7.8%	14.5%
Unexplained variance in 1st contrast =	34.1	6.7%	85.3%

3.4. Reliability

Even though the questionnaire was already tested, the researchers conducted a pilot study on 40 university students to examine the reliability of the study before the actual study. The data of the pilot study were analyzed with the aid of SPSS, and the results showed that each category of the items had an acceptable value of more than 0.75 (Table 4), which indicates high reliability of the instrument.

Table 4. Cronbach’s Alpha Test of Reliability.

Categories	Quantity of items	Cronbach’s alpha value of reliability
Smartphone addiction	10	0.87
Academic performance	10	0.94

3.5. Data collection procedure

The researchers constructed the survey questionnaire through Google form to collect data from the respondents. They shared the link of the questionnaire with the respondents through social networking sites (Facebook, WhatsApp, and Telegram). It was also shared with various online groups with 100s of student members. Furthermore, faculty members were requested to share the link of the questionnaire with their students and request them to take part in the study. In the survey, there was a consent box for the respondents to tick to show their agreement for participation in the study. The questionnaire was open for responses for a month, 21 Feb-2021 to 22 March-2021.

3.6. Data analysis

The researchers imported the data from Google Form to an Excel sheet and then to Statistical Package for Social Sciences (SPSS) to conduct data analysis. Descriptive statistical analysis was used to identify the frequency, percentage, mean, and standard deviation of the data. Inferential statistics (i.e. One-Way ANOVA and Independent Samples t-test) were employed to examine the differences in smartphone addiction between males and females, daily hours of smartphone use, and access to social media. In addition, the study employed Spearman Correlation to figure out the relationship between smartphone addiction and its impact on students’ academic performance.

4. Results

4.1. Daily hours of smartphone usage and access to social media

The study explored students’ daily hours of smartphone usage and access to social media. According to Table 5, 6% of the respondents used smartphones for 0–3 hours per day while around 20% of them used smartphones for 3–5 hours daily. The majority of them (74%) used smartphones more than 5 hours per day. Concerning the participants’ access to social media, 75% of them had access to social media, and only 25% of them did not have access to social media.

Table 5. Daily hours of Smartphone usage and access to social media.

Main variables	Sub-Variables	Frequency	Valid percent
Daily hours of smartphone usage	0–3 Hours	79	6%
	3–5 Hours	271	20%
	More than 5 Hours	971	74%
Total		1321	100%
Do you have Social Media Account?	Yes	994	75%
	No	327	25%
Total		1321	100%

Table 6. Students’ perceptions smartphone addiction.

No	Statement	SD	D	N	A	SA	Sum of A and SA
1	I missed planned work due to use of smartphone.	13.5%	7.5%	14.8%	28.0%	36.3%	64.3%
2	I could not live without having a smartphone.	13.9%	7.1%	15.6%	28.1%	35.3%	63.4%
3	I felt pain in the wrists or at the back of my neck while using a smartphone.	14.5%	9.1%	14.5%	28.8%	33.0%	61.8%
4	I Felt impatient and fretful when using smartphone.	13.9%	7.4%	16.0%	30.1%	32.6%	62.7%
5	I have my smartphone in my mind even when I am not using it.	16.1%	7.4%	15.3%	28.4%	32.8%	61.22%
6	I will never give up using my smartphone even when my daily life is already affected by it.	14.6%	8.3%	15.4%	30.6%	31.1%	61.7%
7	I constantly check my smartphone so as not to miss conversations between other people on Twitter or Facebook.	13.9%	7.0%	15.3%	27.7%	36.2%	63.9%
8	I use my smartphone longer than I had intended.	14.9%	7.6%	15.9%	26.7%	34.8%	61.5%
9	People around me tell me that I use my smartphone too much.	14.6%	7.4%	14.3%	28.5%	35.2%	63.7%
10	I feel calm or cozy while using a smartphone.	13.2%	7.8%	12.6%	30.2%	36.2%	66.4%

4.2. Students’ perception of smartphone addiction

The first 10 items explored students’ perception of smartphone addiction. The results showed that around 64% of the respondents agreed and strongly agreed that they missed their planned work due to smartphone usage, and could not live without having a smartphone. Almost 61% of them accepted that due to use of smartphone, they felt pain in their wrist and neck, and they were impatient and fretful. In addition, 61% of them indicated that even they were not using smartphone, they were thinking about their smartphones and never gave up use of them. Moreover, 63% of them exposed that they were constantly checking their messages and felt calm and cozy while using a smartphone. Furthermore, 64% of them stated that the people around them told them that they used smartphone too much (See Table 6).

4.3. Students’ perception of impact of smartphone addiction on their academic performance

The last 10 items investigated students’ perception of impact of smartphone addiction on their academic performance. The results showed that 64% of the respondents strongly agreed and agreed that due to the excessive use of smartphones, they could not take enough preparation for their final exam, and they neglected doing tasks and projects. Furthermore, 62% of them stated that their academic performance and concentration have been affected by the excessive use of smartphones, and 65% believed that their grades have fallen due to the excessive use of smartphones. Moreover, 64.20% of them believed that they were unable to complete their assignments and other related tasks on time. 63% of them believed that they lost their concentration while doing the activities in the class. Moreover, 66% of them stated that they could not study enough because of excessive use of smartphones. 63% of them indicated that they could not participate in class activities since they were using smartphones excessively. 64% of the respondents stated that the use of smartphone took away their attention from the lecturers in the class. Finally, 65% of them strongly agreed and agreed that due to the excessive use of smartphones, they could not join group activities and pair work (See Table 7).

Table 7. Students’ perception of impact of smartphone on their academic performance.

No	Statement	SD	D	N	A	SA	% of A and SA
1	Due to the excessive use of smartphone, I cannot take much preparation for my final exam.	14.5%	8.0%	13.6%	28.8%	35.0%	63.8%
2	Due to the excessive use of smartphone, I neglect doing tasks and projects.	12.8%	7.3%	16.2%	30.3%	33.4%	63.7%
3	Due to the excessive use of smartphone, my academic performance was negatively affected.	15.1%	7.9%	15.4%	29.4%	32.2%	61.6%
4	Due to the excessive use of smartphone, my grades have started falling.	13.1%	6.8%	15.1%	27.9%	37.1%	65.0%
5	Due to the excessive use of smartphone, I am unable to complete and submit my assignments on time.	13.8%	6.7%	15.4%	29.4%	34.8%	64.2%
6	Due to the excessive use of smartphone, I have a hard time concentrating in class.	12.6%	7.9%	16.7%	28.6%	34.3%	62.9%
7	Due to the excessive use of smartphone, I cannot study enough.	13.9%	5.3%	15.0%	28.9%	36.9%	65.8%
8	Due to the excessive use of smartphone, I cannot participate in the class actively.	13.6%	7.3%	16.3%	27.8%	35.0%	62.8%
9	Due to the excessive use of smartphone, I am unable to pay attention to the lecturers.	13.9%	6.8%	15.3%	28.1%	35.9%	64.0%
10	Due to the excessive use of smartphone, I cannot join group activities in the class.	12.6%	7.3%	15.1%	28.8%	36.2%	65.0%

4.4. Difference of smartphone addiction by respondents’ gender, daily hours of smartphone usage and access to social media

The researchers conducted inferential statistical analysis to determine the impact of the participants’ gender, access to social media and daily hours of smartphone usage on their perceptions of smartphone addiction.

4.4.1. Smartphone addiction by gender and access to social media

Independent samples T-tests were carried out to examine the differences of smartphone addiction by respondents’ gender and access to social media. The results showed that p-value for both variables is less than the alpha level (p = 0.012; p = 0.008 < 0.05). Therefore, it can be concluded that there was a statistically significant difference in smartphone addiction by the respondents’ gender and access to social media (See Table 8).

Table 8. T-test for Differences in Smartphone Addiction by Gender and Access to Social Media.

Variable	Gender	N	Mean	SD	t	df	Sig
Gender	Male	926	3.622	1.30227	−2.059	1319
	Female	395	3.7886	1.44493	−1.975	679.58	0.012
Access to Social Media	Has Account	994	3.7264	1.30768	2.508	1319	0.008
	No Account	327	3.5138	1.39421	2.428	527.494

4.4.2. Smartphone addiction across daily hours of smartphone usage

The researchers conducted One-Way ANOVA test to measure the differences of smartphone addiction across daily hours of smartphone usage. The results revealed that there was a statistically significant difference in smartphone addiction between at least two groups (F(2, 1318) = 78.814, p = 0.000) (See Table 9).

Table 9. ANOVA to determine the difference of smartphone addiction by daily hours of usage.

ANOVA
SMA
	Sum of Squares	Df	Mean Square	F	Sig
Between Groups	217.701	2	108.851	78.814	.000
Within Groups	1820.290	1318	1.381
Total	2037.991	1320

Table 10. Difference between groups.

	N	Mean	Std. Deviation	Descriptive Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
0–2	79	2.7722	.97006	.10914	2.5549	2.9894	1.00	5.00
3–5	271	4.2417	.92380	.05612	4.1312	4.3522	1.00	5.00
6 and Above	971	3.3332	1.25035	.04013	3.2544	3.4119	1.00	5.00
Total	1321	3.4860	1.24255	.03419	3.4189	3.5531	1.00	5.00

4.4.3. Source of difference among groups (0–2 hours, 3–5 hours, 6 or more hours)

To examine the source of difference among different groups (0–2 hours, 3–5 hours, 6 or more hours), the researchers conducted Post—Hoc test. LSD Post Hoc Test for multiple comparisons found that the mean value of smartphone addiction was significantly different between 0 and 2hrs with 3–5hrs (p = 0.000, 95% C.I. = –1.76); 0–2hrs with >6hrs (p = 0.000, 95% C.I. = –0.8307) and 3–5hrs with >6hrs (p = 0.000, 95% C.I. = 1.1748) (Tables 11–12).

Table 11. Multiple Comparisons (LSD).

(I) DailyHour	(J) DailyHour	Mean Difference (I-J)	Std. Error	Sig	95% Confidence Interval
					Lower Bound	Upper Bound
0–2	3–5	−1.46955*	.15026	.000	−1.7643	−1.1748
	6 and Above	−.56101*	.13749	.000	−.8307	−.2913
3–5	0–2	1.46955*	.15026	.000	1.1748	1.7643
	6 and Above	.90854*	.08074	.000	.7501	1.0669
6 and Above	0–2	.56101*	.13749	.000	.2913	.8307
	3–5	−.90854*	.08074	.000	−1.0669	−.7501

* . The mean difference is significant at the 0.05 level.

Table 12. Spearman Correlation.

Correlations
			Mean-Addiction	Mean-Academic
Spearman’s rho	Mean-Addiction	Correlation Coefficient	1.000	−.770**
		Sig. (2-tailed)	.	.000
		N	1321	1321
	Mean-Academic	Correlation Coefficient	−.770**	1.000
		Sig. (2-tailed)	.000	.
		N	1321	1321

** Correlation is significant at the 0.01 level (2-tailed).

4.5. Correlation between smartphone addiction and its impact on students and their academic performance

Spearman correlation analysis was carried out to identify whether there was any relationship between the smartphone addiction and its impact on students and their academic performance. Table 12 shows that the p-value for both variables is less than the alpha value (p = 0.000 < 0.05). Therefore, it can be concluded that there was a strong negative correlation between smartphone addiction and its impact on students and their academic performance.

5. Discussion

Smartphone addiction is a disorder involving compulsive overuse of mobile devices, usually quantified as the number of times users access their devices or the total amount of time they are busy working with their mobile devices. This study aimed at investigating undergraduate students’ perceptions of smartphone addiction and its impact on their academic performance. The results showed that the participants used smartphones to varying extent on a daily basis, and most of them had access to social media. It is on par with the study by Orfan (2021) who reported that young people in Northeastern Afghanistan used 2–3 hours of their time on social media especially Facebook every day. The findings also showed that students used their smartphones frequently and they were highly addicted to them. The majority of the students indicated that due to the excessive use of smartphones, they missed their planned work and felt pain in the wrists or at the back of the neck. These findings are in line with the studies carried out by Alhassan et al. (2018), Arefin et al. (2017), Bağcı and Pekşen (2018), Boumosleh and Jaalouk (2018), García-santillán and Espinosa-ramos (2021), Ifeanyi and Chukwuere (2018), Kibona and Rugina (2015), Ma et al. (2020), Mukhdoomi et al. (2020), Nayak (2018), Yalçı et al. (2020) and Sachitra (2015) who found that the students were highly addicted to the use of smartphone.

The majority of the participants believed that excessive use of smartphones had a negative impact on their academic performance. They indicated that their excessive use of smartphones has led to their low interest in taking part in the classroom. These findings are consistent with those of the studies by Cao et al. (2018b), OZER (2020), Ahmed et al. (2020), Nayak (2018), Khan et al. (2019) and Arefin et al. (2017), and Hashemi (2021b), who found that the excessive use of smartphone had a negative impact on the academic performance of students The study also revealed that most of the participants lost their concentration in the class due to excessive use of smartphones. This finding is similar to that of the study by Orfan (2022) who reported that lecturers’ use of smartphones in the class for non-education purposes offended students, which may result in their decline of concentration. The use of social media and smartphone among university students in Afghanistan is new compared to other countries since the country has encountered decades of war and instabilities, even there is no telephone coverage in some parts of the country and people are unfamiliar with the use of smartphone (Noori et al., 2022; Noori & Noori, 2021).

The current study found that there were statistically significant differences in smartphone addiction between males and females. Female respondents were addicted to smartphone more than male students. This finding supports that of the studies carried out by Sachitra (2015), Aljomaa et al. (2016), Kibona and Rugina (2015), Ahmed et al. (2020) and García-santillán and Espinosa-ramos (2021) who explored gender differences in smartphone addiction and indicated that female students were tend to use their smartphone more often than the male students. However, it contradicts the findings of the study by Chen et al., (2017), Yang et al., (2018) and Nayak (2018), who reported that male students used smartphones more frequently than female students did. It is also inconsistent with the finding of a study conducted by Hawi and Samaha (2016) who found no significant differences in the use of smartphone between male and female students. The difference can be accounted for by the fact that some male students are the breadwinners of their families in Afghanistan and some have to work to support their studies; they have to work part-time to provide for their families and support their studies. Therefore, they may not have much time to use smartphones. On the other hand, very few female students may work during their studies at university, which leaves them ample time.

The study also found that there was a statistically significant difference in smartphone addiction based on students’ access to social media. Students who accessed social media were more likely addicted to smartphone than those who did not. This finding is aligned with the findings of the studies conducted by Gezgin (2018), Bağcı and Pekşen (2018), Sabbah et al. (2019), Cao et al. (2018a), Boumosleh and Jaalouk (2018), Chua et al. (2020) and Lau (2017) whose findings indicated that individuals accessing social media were more likely addicted to smartphone than those who did not access social media. In addition, the current study revealed that there was a statistically significant difference in smartphone addiction by students’ daily hour of smartphone usage. Students who dedicated more hours of their time for the use of smartphones were highly addicted to the smartphone than those who dedicated their less time for the use of smartphone. This finding is consistent with the findings of the studies carried out by Aljomaa et al. (2016), Mukhdoomi et al. (2020) and Aljomaa et al. (2016) who reported that there were statistically significant differences in smartphone addiction according to the daily hours dedicated to the use of smartphone, those who used a smartphone for a long period were more likely addicted to their smartphone.

The current study found that there was a significant negative correlation between smartphone addiction and its impact on students and their academic performance. It supports the studies carried out by Kibona and Magay (2015), Boumosleh and Jaalouk (2018), Yalçı et al. (2020), Iyito and Çeliköz (2017), Khan et al. (2019), Hawi and Samaha (2016) and Samaha and Hawi (2016) who reported a negative correlation between smartphone addiction and its impact on students’ academic performance. However, this finding contradicts several other studies carried out by Aljomaa et al. (2016), Ifeanyi and Chukwuere (2018) and Kibona and Rugina (2015) who reported a strong positive correlation between smartphone addiction and its impact on students’ academic performance. This dissimilarity can be explained by the fact that people in various countries use smart phones for various purposes. Smartphone users may be of lower awareness about the consequences of overuse of smartphones. Most of the users may use smartphones to access social media, listen to music, watch films, play games, text with others, call friends and take photos because of high price of Internet data and poor Internet connection. However, users in other countries may use smartphones to collaborate with their peers, complete their homework, and access the information quickly.

6. Conclusion

Nowadays smartphone addiction is a big problem among university students in Afghanistan. Students in today’s educational settings often overuse smartphones and it seems to be a serious concern for instructors and parents. Therefore, the current study aimed at investigating undergraduate students’ perception of smartphone addiction and its impact on themselves and their academic performance. The study found a negative impact of smartphone addiction on the academic performance of Afghan students. In addition, significant differences were found in smartphone addiction according to the participants’ gender, access to social media and hours they spent using smartphone. It was also found that there was a strong negative correlation between students’ perception of smartphone addiction and its impact on themselves and their academic performance.

The study has implications for lecturers, higher education institutions and the Ministry of Higher Education. Lecturers should have specific policies on their syllabi about the use of smartphones in the classrooms. In order to maintain students’ concentration to the class activities, lecturers should specify when students can and cannot use smartphones in the classroom. Higher education institutions with the coordination of the Ministry of Higher Education (the managing and policymaking entity of higher education in Afghanistan) should develop and implement a policy to address the overuse of smartphones in public dormitories and on campuses in order to help students achieve the intended learning outcomes. Furthermore, universities should support student organizations to raise awareness about the negative consequences of the overuse of smartphones.

The study had some limitations. The researchers used an online-based survey questionnaire to collect data from the participants. Thus, it was not representative of students without access to the Internet. Furthermore, the data were collected from five universities based in Takhar Province, a northeastern province of Afghanistan. It may not be generalizable to all public and private universities in Afghanistan. Further studies with samples from various pubic and private universities from different regions of Afghanistan are required to obtain a deeper insight of smartphone addiction and its impact on students’ academic performance in higher education institutions in Afghanistan. Future studies should use various instruments (e.g. interviews) to collect data from participants. Experimental studies may be conducted to see whether there is a connection between a particular activity of students while using a smartphone (e.g. calling/texting friends for questions related/unrelated to one’s studies, playing cognitive/non-cognitive games) and academic performance.

Disclosure statement of funding

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Aminuddin Hashemi

Aminuddin Hashemi is a senior lecturer in the English department of Takhar University, Afghanistan. He earned his Master’s degree in TESL from Universiti Teknologi Malaysia (UTM). Mr. Hashemi has published many research papers and participated in various national and international conferences. He also supervised more than 50 bachelor’s degree monographs in the department of the English language. His research interests are teaching and learning, Teaching English as a Foreign Language (TEFL), Technology Enhanced Language Learning (TELL), Computer Assisted Language Learning (CALL), Mobile Assisted Language Learning (MALL), Online Teaching and Learning, Learning Analytics (LA), Critical Discourse Analysis (CDA), etc. He is also interested in using various technological tools and applications in EFL classrooms.

Abdul Qawi Noori

Abdul Qawi Noori is a PhD student at Monash University. His areas of research are teaching and learning, data-driven decision-making, school effectiveness, quality assurance and quality management in higher education, and technology in teaching and teaching English as a second language.

Sayeed Naqibullah Orfan

Sayeed Naqibullah Orfan is a PhD student at the University of Toronto. He is an activist and advocate of gender equality in Afghanistan. His areas of research are language attitudes, language, and gender, learning in higher education, outcome-based education, and student-centered learning.

Sayeed Asif Akramy

Sayeed Asif Akramy is currently an English tutor at Warwickshire College in the United Kingdom. He has a master’s degree in TESOL. He has taught English for over ten years in different national and International sectors. His areas of research are language teaching and learning, language attitudes, and student-centeredlearning.

Mohd Rustam Mohd Rameli

Mohd Rustam Mohd Rameli is a senior lecturer at the School of Education, Faculty of Social Sciences and Humanities at Universiti Teknologi Malaysia where his teaching and research focus on positive psychology including well-being, mental health, and motivation