Exploring the role of smartphone use and demographic factors in predicting nomophobia among university students in Jordan

ABSTRACT

Nomophobia is one of the problems of the overuse of mobile phones and the fear of missing out, which has become prevalent among university students and interferes with their daily activities. This study aimed to investigate the extent and potential predictors of nomophobia among university students, including the role of smartphone use and demographic factors. The study surveyed 636 students from various academic levels using the Nomophobia Questionnaire (NMP-Q) through an online cross-sectional survey. The results showed that nomophobia varied in severity from mild to severe. Females experienced nomophobia more frequently than males (p < .001). Gender, phone-checking frequency, number of calls made and received per day, and number of texts received per day were all predictors of nomophobia. With such knowledge, targeted interventions and support systems can be developed to cater to these students’ unique requirements and struggles regarding smartphone use and nomophobia.

KEYWORDS:

• Smartphone use
• nomophobia
• university students
• attitudes
• prevalence
• gender

Introduction

Smartphones have become an integral part of everyone’s daily lives. While technological improvements have provided many advantages, they have also created new psychological challenges. Nomophobia, or the anxiety of being without or unable to utilize a mobile device, is one such challenge (King et al., 2014a, 2014b; Olivencia-Carrión et al., 2018; Park et al., 2019). Data showed that more than 6.6 billion people use smartphones for communication, web browsing, and entertainment (O’Dea, 2021). Recent years have witnessed technological addiction, such as addiction to computer games, internet-based gambling disorders, and internet addiction (Darvesh et al., 2020; Geisel et al., 2021; Kuss & Pontes, 2018).

The term ‘nomophobia,’ the excessive use of smartphones, has emerged as a form of technological addiction which become a global concern (Caprì et al., 2021; Fabio & Suriano, 2021; Fabio et al., 2022; Panova & Carbonell, 2018). Nomophobia is a fear that cannot be controlled when leaving home without ‎a mobile phone. This fear of disconnection can cause anxiety and affect the level of concentration (Harish & Bharath, 2018). Addiction was defined as a behaviour that elicits pleasure and, through repetitive exposure, progressively results in loss of self-control and consequent adverse outcomes (Eide et al., 2018). Later, King et al. (2014b) proposed a new definition of nomophobia, focusing on the contextual nature of fear, specifically for mobile phones. The new definition considered nomophobia a situational phobia and includes a broader range of behaviours and symptoms associated with mobile phone use.

Nomophobia has arisen as a relevant issue among university students, with mental health specialists concerned about its prevalence. Several studies have found that this group has a significant prevalence of nomophobia (Alhassan et al., 2018; Gutiérrez-Puertas et al., 2018; Yildirim & Correia, 2015). A systematic review and meta-analysis study evaluating 20 papers, consisting of 12,462 participants, revealed that the prevalence of moderate to severe nomophobia was 70.76%, and severe nomophobia was 20.81%. According to this review, university students composed the highest group affected by a prevalence of severe nomophobia, with 25.46% affected (Humood et al., 2021).

In India, multiple studies have explored the prevalence of nomophobia among college students, with results ranging from 24.1% to 99% (Dongre et al., 2017; Mallya et al., 2018). Similarly, a study in Saudi Arabia found that nomophobia was common among students, affecting 85.3% of respondents (Hassan et al., 2019). Another study (Alahmari et al., 2018) reported that 22.2% of students had severe nomophobia. A survey of university students in Kuwait indicated that none of the subjects were completely free of nomophobia, and 92 (18.0%) and 288 (56.2%) participants reported mild and moderate fear. Furthermore, a quarter of the sample, or 132 students (25.8%), had severe nomophobia (Al-Balhan et al., 2018).

Smartphone use is crucial in understanding the development and maintenance of nomophobia among university students. The frequent availability and reliance on mobile phones for social media participation, instant messaging, internet browsing, and academic pursuits add to the fear of being without them (Thomée, 2018). The addictive behaviours linked with excessive smartphone use establish a dependency that exacerbates nomophobia (Deleuze et al., 2015). This smartphone addiction can have a negative impact on mental health outcomes, such as increased stress, decreased academic performance, and disrupted sleep patterns (Cain & Malcom, 2019; Darvishi et al., 2019; Demirci et al., 2015; Elhai et al., 2018; Gezgin et al., 2018; Long et al., 2016).

According to Shambare (2012), cell phones are potentially the most serious non-drug addiction in the twenty-first century. College students spend more than 9 hours daily on their cell phones, leading to addiction. This phenomenon highlights technology’s paradoxical nature as a liberating force from the actual world and a mesmerizing one that entraps persons in the virtual sphere (Salehan & Negahban, 2013). According to Mahapatra (2019), smartphone addiction is caused by feelings of isolation, self-regulation issues, conflicts in personal and familial relationships, and poor academic performance.

Smartphone addiction is similar to other addictive disorders, but cell phones’ compact, portable nature increases the related hazards (Lin et al., 2014, 2015). Problematic smartphone use is influenced by learning mechanisms, with conditioning principles contributing to the behaviour becoming ingrained and mostly subconscious (Busch & McCarthy, 2021; Duke & Montag, 2017a, 2017b). However, not everyone responds the same way to these principles, with individuals inclined to intermittent reinforcement feeling a greater influence. In this comparison, the smartphone is like a slot machine, satisfying us with interesting messages via platforms like WhatsApp or emails on an irregular and unpredictable basis, creating a strong pattern of smartphone engagement (Duke & Montag, 2017a, 2017b).

Implementing smartphone limits for excessive usage may result in withdrawal symptoms that impair productivity, social interactions, physical well-being, and emotional well-being. A study conducted by Eide et al. (2018) involved 127 volunteers aged between 18 to 48 years. The volunteers were randomly assigned to either a restricted or controlled group. During the 72 hours of smartphone restriction, the participants were asked to complete the Smartphone Withdrawal Scale (SWS), the Fear of Missing Out Scale (FoMOS), and the Positive and Negative Affect Schedule (PANAS) three times a day. The study found that individuals who were restricted from using their smartphones displayed more withdrawal symptoms and a higher fear of missing out than those who were not restricted (Eide et al., 2018; Horwood & Anglim, 2021; Richardson et al., 2018).

Recently, Moretta et al. (2022) proposed a theoretical framework to understand problematic smartphone and internet usage. They highlighted the significance of focusing on the behaviour instead of the individual and introduced cognitive-behavioural models, including Davis’s (2001) model with two components and Caplan’s (2010) modification that added cognitive and behavioural variables. Brand et al. (2014) suggested that dysfunctional prefrontal control mechanisms are linked to impaired self-regulation and coping strategies, which may lead individuals to seek solace in the online world. The Interaction of Person-Affect-Cognition-Execution (I-PACE) model (Alotaibi et al., 2022; Lim, 2018; Zou et al., 2022) explains problematic internet use (PIU) behaviours through the interactions between predisposing factors, moderators, and mediators. The interwoven nature of internet and smartphone use makes it challenging for individuals to discontinue problematic behaviours. Therefore, it is essential to examine the relationship between problematic smartphone use (PSU) and withdrawal symptoms, both at the behavioural and cognitive dimensions (Lee et al., 2017).

The findings of Mir and Akhtar’s (2020) study revealed important insights into the impact of reducing mobile phone usage on anxiety levels. As predicted, the results showed a significant increase in state anxiety levels over time among participants with moderate nomophobia who were not in contact with their mobile phones. This shows that limiting mobile phone use may increase anxiety in this demographic. The study, on the other hand, found that cognitive and sensory diversions had just a minor effect on delaying anxiety in fearful situations. While diversions may momentarily reduce anxiety, their influence appears limited, showing that the underlying nomophobia-related anxiety continues even when distractions are present.

Gender, study major (health or non-health), academic year, and smartphone use pattern have all been studied as predictors of student nomophobia. However, the literature on gender differences in nomophobia is inconsistent (Aldalalah, 2020; Dongre et al., 2017; Gezgin et al., 2018; Mallya et al., 2018; Yildirim et al., 2016). For example, a study among medical students showed that the prevalence of nomophobia was higher ‎among female university students (64.2%) than that of male students (35.7%) (Mallya et al., 2018). However, other findings indicated that nomophobia was significantly lower in females than in males (Aldalalah, 2020; Cain & Malcom, 2019). In contrast, a recent study among students in Oman found no difference between males and ‎females in Nomophobia (Qutishat et al., 2020).

On the other hand, the study major has been demonstrated to influence students’ vulnerability to nomophobia. A study in Bengal showed that male engineering students are at a higher risk of nomophobia (42.7%) than male students in medical colleges (34%). Female students in engineering college are less prevalent (53.8%) than female medical college students (57.8%). The difference may also be at different medical specialities’ levels (Dasgupta et al., 2017). A study found that Pharmacist students are (27.5%) more likely to have severe nomophobia than dentistry students (20%) and medical students (15.8%) (Hassan et al., 2019).

The educational level and academic year have different effects on students’ levels of nomophobia. Nomophobia is often more common among medical students with higher educational status (Darvishi et al., 2019). As for the academic year, the prevalence of nomophobia among first and second-year students was less than among third-year and above students (Dasgupta et al., 2017). However, a study among Pakistani and Turkish undergraduate Students (Özdemir et al., 2018) indicated that students classified as nomophobia were topped by first-year students (39.1%), then fourth-year students (31.3%). Furthermore, the daily hours spent using a smartphone determine the extent of a person’s addiction to a mobile phone. A study indicated that students who use mobile phones more than two hours a day are rated as having severe nomophobia, and students who use the phone daily for one to two hours received a score of mild Nomophobia (Hassan et al., 2019).

The prevalence and causes of nomophobia have received much attention among university students, who rely heavily on smartphones for communication, socializing, and academic purposes. Nomophobia has arisen as a potential threat to student’s mental health and overall functioning. Understanding the degree of nomophobia in this population and its predictors is critical for designing tailored therapies and support networks. The aim of this study was to investigate the prevalence of nomophobia among university students, explore the factors contributing to its occurrence, and specifically examine the role of smartphone usage patterns and demographic characteristics in understanding and addressing this phenomenon. This study addressed the following research hypothesis:

H1:

The prevalence of nomophobia among university students is positively associated with the frequency and duration of smartphone use.

H2:

The dimensions of nomophobia will vary based on students’ gender, with a stronger association observed within specific demographic groups.

H3:

The level of nomophobia among university students will vary based on their gender, duration, and smartphone use patterns, including the frequency of phone use, phone checks, number of calls, messages, emails, and applications, with a stronger association observed among specific groups.

Methods

Study design and procedure

An anonymous, voluntary online cross-sectional survey was conducted to collect data from 636 smartphone users at various universities in Jordan, regardless of their major or level of study. The accessible population comprised all undergraduate and postgraduate students who accessed and agreed to participate in the survey. Participants must be students (in any programme/track or study level) in public and private universities and use smartphones.

Ethical approval for the study was obtained from the author’s Institutional Review Board (Ref: 29/132/2020, dated 25/4/2020). The Google Forms link was shared on social media platforms (e.g. Facebook and Twitter) and online forums (Students’ Union and a group of graduate students) between June and November 2020. Before the survey’s commencement, a brief introductory message was posted to explain the study’s nature, purpose, potential risks, and procedures.

Measures

Demographic data

The demographic information consists of five components: gender, study major (health or non-health), educational attainment (bachelor’s, master’s, or doctoral), study year (first, second, third, fourth, or higher), and smartphone accessibility.

Smartphone use

This section, based on YYildirim and Correia’s (2015), includes questions about smartphone ownership duration, data plan ownership, average daily usage time, frequency of checking, number of phone calls and text messages sent/received per day, number of emails sent/received per day, and number of applications on the smartphone. This section included questions about the different purposes of use and the context in which the smartphone is used. ‎

Nomophobia questionnaire (NMP-Q)

Nomophobia was measured using the Nomophobia Questionnaire (NMP-Q), a scale developed by Yildirim and Correia (2015). The NMP-Q is the only psychological instrument to investigate the construct of nomophobia. In this study, an Arabic version of NMP-Q was validated by Al-Balhan et al. (2018) among a sample of university students in Kuwait. This instrument consists of 20 questions divided into the four factors that assess the dimensions of nomophobia: not being able to communicate, losing connectedness, not being able to access information, and giving up convenience. The response was graded on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Cronbach’s alpha coefficient for the original instrument was .918 (Yildirim & Correia, 2015), and for the Arabic version was 0.879. Cronbach’s alpha for the current study was 0.935.

Based on the overall score and considering the cut-off values proposed by Al-Balhan et al. (2018), participants were subdivided into subjects without Nomophobia (NMP-Q score equal to 20), with mild (NMP-Q score in the range 21–60), moderate (NMP-Q score in the range 60–100), and severe Nomophobia (NMP-Q score was in the range 100–140).

Data analysis

The data analysis was conducted using the Statistical Package for Social Science (SPSS) version 25. Descriptive analyses such as means, standard deviations, and percentages were used to assess the students’ demographics. The sum of the items for nomophobia was used to classify the levels. Independent sample t-tests and one-way ANOVA were used to examine the associations between students’ attitudes and various demographics, such as gender, level of education, academic year, and study major. One-way MANOVA was also used to test the effects of gender on the four factors of nomophobia. Multiple linear regression analysis was performed to identify the predictors of students’ attitudes and nomophobia. The significance level was set at p < 0.05.

Results

Characteristics of study participants

The demographic characteristics of the study participants are presented in Table 1. A total of 636 students took part in the survey. Among the participants, 53.1% (n = 338) were female, 77.5% (n = 493) were undergraduates, and 57.4% (n = 365) were not in the medical field. Most students (71.4%, n = 454) were enrolled at a public institution, and over 32.4% (n = 206) were in their fourth year. Approximately two-thirds of the students (66.2%, n = 421) reported using smartphones for more than five years, and most students (83.6%, n = 532) reported checking their phones at least once every 30 minutes (Table 1).

Table 1. Characteristics of the study participants (N = 636).

Item	Category	n	%
Gender	Male Female	298 338	46.9 53.1
Study major	Medical Non-medical	271 365	42.6 57.4
University type	Public Private	454 182	71.4 28.6
Educational level	Bachelor Master & Doctorate	493 143	77.5 22.5
Study years	1^st year 2^nd year 3^rd year 4^th year & above	91 192 147 206	14.3 30.2 23.1 32.4
The duration of phone use	2 to 3 years and less 4 to 5 years More than five years	52 163 421	8.2 25.6 66.2
Having mobile data	Yes No	625 11	98.3 1.7
Frequency of checking phone	Every 30 minutes or less Every hour Every 2 hours or more	532 56 48	83.6 8.8 7.5

Smartphone usage patterns

On average, students use their phones for 7.9 hours per day, ranging from one to twenty-four hours. Sending and receiving text messages were the most consuming activities, with an average of 60.60 (SD = 229.53) messages sent and 121.84 (SD = 229.53) received daily. Students reported having at least 23 phone apps (Table 2).

Table 2. The pattern of smartphone use per day.

Item	M	SD
Time spent using the phone	7.92	3.94
Number of phone calls made	4.49	4.49
Number of phone calls received	5.08	4.43
Number of text messages sent	60.60	154.95
Number of text messages received	121.84	229.53
Number of emails sent	4.83	44.72
Number of emails received	5.02	17.76
Number of apps on the phone	23.36	17.19

Purpose of smartphone usage

The most common reasons for using a smartphone were social media (98.9%), texting family or friends (98.4%), searching for information on the internet (98%), and talking with family or friends (97.8%) (Table 3).

Table 3. The purpose students use the smartphone.

For which of the following purposes do you use your smartphone?^a	Responses
	N	%
Checking email	492	8.3
Looking information up on the Internet	623	10.6
lecture notes	419	7.1
Listening to music	527	8.9
social media	629	10.7
Scheduling meetings and events	389	6.6
Gaming	443	7.
Talking with family or friends	622	10.5
Getting news	580	9.8
Texting family or friends	626	10.6
Killing time	546	9.3

a. Dichotomy group tabulated at value 1=yes.

Context of smartphone usage

Students were most likely to use their smartphones when feeling bored (97.3%, n = 618), when alone (95.4%, n = 606), or when waiting for someone or something (95.1%, n = 604). While driving, students used their phones the least (25.2%, n = 160) (Table 4).

Table 4. The contexts in which the students used their smartphones.

Context^a	Responses
	n	%
At a dinner table	225	5.1
When I’m bored	618	14.0
While hanging out with friends	311	7.1
During a class	230	5.2
While talking to somebody	213	4.8
In the restroom	251	5.7
While waiting for someone or something	604	13.7
On public transportation	529	12.0
While walking	322	7.3
While driving	160	3.6
While watching TV or a movie	340	7.7
When I’m alone	606	13.7

a. Dichotomy group tabulated at value 1=yes.

Levels of nomophobia

The average nomophobia score was 98.25 (SD = 25.17), ranging from 32–140. According to the cut-off values proposed by Yildirim and Correia (2015), the severity of nomophobia ranged from mild (11.3%, n = 72) to moderate (47.2%, n = 300) to severe (41.5%, n = 264). Table 5 shows that ‘Giving up convenience’ had the highest mean score (M = 33.38, SD = 9.59) among all dimensions of nomophobia, followed by ‘inability to communicate’ (M = 25.1, SD = 8.02), and ‘loss of connectedness’ (M = 23.78, SD = 8.99). On the other hand, ‘not being able to access information’ had the lowest score (M = 11.03, SD = 2.59).

Table 5. Description of nomophobia dimensions.

Nomophobia dimensions	M	SD	Minimum	Maximum
Not being able to communicate (FACTOR I)	25.09	8.024	5	35
losing connectedness (FACTOR II)	23.78	8.990	6	42
Not being able to access information (FACTOR III)	11.03	2.598	2	14
Giving up convenience (FACTOR IV)	33.38	9.594	7	49

Nomophobia and the effect of demographic and academic variables

Results of the independent samples t-test showed a significant effect of gender (t (2,634) = −4.60, p < .001), with female students (M = 97.52, SD = 25.61) having higher mean nomophobia scores than male students (M = 88.46, SD = 23.81). However, no significant effects were found for study major, type of university, and educational level (p = .233, .432, .914, respectively) (Table 6).

Table 6. Nomophobia and the effect of demographic and academic variables.

Variables	Category	M	SD	P (t,F)
Gender	Males	88.46	23.81	p < .001*
	Females	97.52	25.61
Study Major	Medical	91.89	25.14	.233
	Non-medical	94.30	25.18
University type	Public	92.78	25.56	.432
	Private	94.52	24.19
Educational level	Bachelor	93.22	25.02	.914
	Master & Doctorate	93.48	25.77
Study years	1^st year	95.89	24.12	.37
	2^nd year	94.86	24.90
	3^rd year	92.17	25.14
	4^th year and above	91.43	25.88
The duration of phone use	2 to 3 years	101.21	25.45	.008**
	4 to 5 years	89.28	26.15
	>5 years	93.84	24.52
Frequency of checking the phone	Every 30 minutes and less	96.72	24.20	p < .001**
	Every hour	81	23.64
	Every 2 hours and more	69.42	19.87

*significant value of t-test of independent samples,** significant value of F ratio..

Further analysis revealed that the length of time students used their phones was a significant factor (F (2,633) = 4.80, p = .008) (Table 6). Tukey’s post hoc test of significance showed that students who had used their phones for three years or less (M = 101.21, SD = 25.45) had significantly higher mean scores of nomophobia than those who had used their phones for four to five years (M = 89.28, SD = 26.15), p = .008.

There was also a significant association between the frequency of checking phones and nomophobia scores among students (F (2.633) = 36.94, p < .001) (Table 6). Post hoc comparisons indicated that students who checked their phones every 30 minutes had a higher mean score of nomophobia than those who checked their phones every hour (96.72 vs. 81.00, p < .001) and for more than 2 hours (96.00 vs. 69.42, p = .037). Moreover, students who checked their phones every hour had higher mean nomophobia scores than those who checked their phones every two hours (81.00 vs. 69.42, p = .037).

Moreover, the study found significant multivariate effects of gender on the four factors of nomophobia (F (4, 631) = 8.041, p < .0005; Wilk’s Λ = 0.951, partial η^2 = .049). Specifically, female students had higher mean scores than male students in Factor I (M = 31.19 (9.33) Vs. M = 27.66 (9.39)), Factor II (M = 20.99 (8.11) Vs. M = 18.75 (7.44)), and Factor IV (M = 24.62 (7.42) Vs. M = 21.97 (6.90)), but there was no effect on Factor III (p = .099) (Table 7).

Table 7. Significant univariate effects for gender on four factors of nomophobia.

Dependent Variable	Gender	M	F	p values	95% CI
					Lower Bound	Upper Bound
FACT-I^a	Male	27.661	22.535	p < .0005	26.596	28.726
	Female	31.192			30.192	32.192
FACT-II^b	Male	18.755	13.054	p < .0005	17.867	19.643
	Female	20.997			20.163	21.831
FACT-III^c	Male	20.067	2.737	.099	19.511	20.623
	Female	20.710			20.188	21.232
FACT-IV^d	Male	21.977	21.468	p < .0005	21.159	22.794
	Female	24.621			23.854	25.389

Not being able to communicate^,a losing connectedness^,b Not being able to access information^,cGiving up convenience^.d.

Predictors of nomophobia severity in college students

Multiple linear regression was conducted to predict nomophobia based on students’ gender and smartphone use patterns, including the frequency of phone use, phone checks, time since last use, number of calls, messages, emails, and applications. The results indicated a significant regression equation (F (11, 635) = 16.20, p < .001), explaining 22.2% of the variance (R^2 = 0.222). Gender (ß = −0.189, p < .001), frequency of phone checks (ß = −0.257, p < .001), daily phone calls (ß = 0.157, p = .007), and daily text messages (ß = 0.185, p = .001) were significant predictors of students’ levels of nomophobia (Table 8). Specifically, female students were more likely to experience nomophobia than male students. Students who checked their phones every 30 minutes were found to have a higher likelihood of experiencing nomophobia. Moreover, the number of text messages received and phone calls made positively correlated with nomophobia scores.

Table 8. Factors predicting nomophobia (N = 636).

Independent variables	B	BSE	β	t	P	95%CI for B
						Lower	Upper
Gender	9.506	‎1.900	‎.189‎	5.002	p < .001	5.77	13.23
Time spent using the phone	.332	‎.257	‎.052‎	1.29	.198	−.173	.837
Frequency of checking the phone	−11.20	‎1.67‎	‎-.257‎	−6.69	p < .001	−14.487	7.917
The duration of phone use	1.85	‎1.41‎	‎.047‎	1.30	.191	−.927	4.634
Number of phone calls made	.881	‎.328‎	‎.157‎	2.68	.007	.237	1.526
Number of phone calls received	−.280	‎.334‎	‎-.04	−.838	.402	−.935	.376
Number of text messages sent	.007	‎.009‎	‎.042‎	.769	.442	−.011	.024
Number of text messages received	.020	‎.006‎	‎.185‎	3.41	.001	.009	.032
Number of emails sent	−.011	‎.023‎	‎-.020‎	−.485	.628	−.056	.034
Number of emails received	−.091	‎.055‎	‎-.064‎	−1.63	.102	−.199	.018
Number of apps on the phone	.093	‎.054‎	‎.063‎	1.71	.088	−.014	.200
Constant	78.09	6.21	-	12.56	p < .001	65.889	90.295

R² = 0.22, F-ratio = 16.20, the unstandardized beta (B), the standardized beta (β), standard error for the unstandardized beta (SE B), R²: R Square.

Discussion

Based on our findings, most students reported experiencing moderate to severe levels of nomophobia. Giving up convenience had the highest mean score among all dimensions of nomophobia, followed by inability to communicate and loss of connectedness. However, not being able to access information had the lowest score. These results align with previous research (Aldalalah, 2020; Bartwal & Nath, 2020; Gezgin, 2017; Yildirim et al., 2016).

Giving up convenience and losing connectedness refers to distancing oneself from one’s online identity, particularly through social media, which is how students typically communicate with family and friends. Losing this connection can jeopardize their sense of identity and lead to feelings of missing out. The various dimensions of nomophobia identified in previous studies may stem from differences in students’ perceptions of the impact of smartphone use and their level of dependence.

As per the study, students spent more than 8 hours daily on their phones and checked them every 30 minutes or less. The most common reasons for smartphone usage were social media, texting/talking to family or friends, and browsing the internet for information. The phones were primarily used when students felt bored, were alone, or were waiting for something/someone. However, they were less likely to use their phones while driving. These findings are consistent with previous studies, which also reported high average time spent on smartphones by participants (Bartwal & Nath, 2020; Buctot et al., 2021; Demir, 2019; Gowda et al., 2019; Kalaskar, 2015; Kara et al., 2021; Vicdan & Baybuga, 2019). Such excessive usage is worrisome, indicating that students spend more time on smartphones than on other important activities like exercise and sleep. Overuse or misuse of smartphones negatively affects students’ mental and physical well-being. Those relying on smartphones frequently are more prone to psychological issues such as insomnia, loss of interest/motivation in studies, anxiety, and stress related to nomophobia (DataReportal, 2021).

According to the results of this study, the most prevalent reason for students to use their phones is social networking. Popular social media platforms such as Facebook, Instagram, Twitter, Snapchat, WhatsApp, and YouTube each have features that draw students in. These platforms allow students to create free profiles, pages, and groups, track pages, and follow any desired topic. Social networking sites are linked to a user’s phone number or laptop, allowing them to send text messages and share videos, voice messages, and photographs with their connections via the internet. Social media growth has ‎increased since the outbreak of COVID-19. Students rely more frequently on social media as a ‎source of information and communicate with university instructors, friends, and family. There ‎are now 4.20 billion social media users around the ‎world. This figure has grown by 490 million ‎over the past 12 ‎months, delivering year-on-year growth of more than 13% (DataReportal, 2021). Therefore, social media are virtual platforms that provide wide-ranging ‎services to communicate with relatives and friends through calls and messages.

This study showed that nomophobia was higher for female and male ‎students. This result corresponds with the results of many previous studies (Gowda et al., 2019; Gutiérrez-Puertas et al., 2019; Mallya et al., 2018; Yildirim et al., 2016). However, some inconsistent results revealed ‎that males than females have nomophobia (Yildiz et al., 2020; Takao et al., 2009). Females are more dependent on Internet services and more likely to become ‎addicted to smartphones (Kalaskar, 2015). Females are less likely to ‎participate in outdoor activities and events and enjoy building relations with ‎friends on social media (Slaih et al., 2019). They also use their smartphones in public settings more frequently to escape feelings of loneliness. Males, on the other hand, use their phones more for professional and technological purposes than for socializing. Moreover, females are more anxious than males if they cannot keep up to date ‎with social media (Mallya et al., 2018).

According to earlier research (Aldalalah, 2020; Dasgupta et al., 2017; Gezgin, 2017; Gowda et al., 2019), the frequency of phone checking, number of calls made, and number of text messages received per day were significant predictors of nomophobia among students. Smartphones have become vital tools for students, allowing them to communicate, make video conversations, and send audio messages via numerous apps. On the other hand, unrestricted access to these services promotes a persistent desire to check phones, leading to unconscious browsing and notification checking (Gowda et al., 2019). As students rely on their phones for academics and examinations, the COVID-19 lockout has increased smartphone usage. Furthermore, because many college students live alone, smartphone access to the internet and social media is critical for remaining connected and minimizing feelings of loneliness, anxiety, and restlessness induced by broken routines and lost relationships.

Limitations

Although this study provided evidence supporting the research hypothesis, it is important to acknowledge its limitations. One of the main limitations is that the study was conducted during a lockdown, which could have influenced the students’ smartphone use and level of nomophobia. Additionally, although the study had a large sample size, the subgroups may not have been fully representative. For ‎example, an inadequate number of graduate and postgraduate students participated in this study, ‎in which the differences between groups were not well defined. Another limitation is that the online surveys were open to anyone, which may have resulted in biased responses due to misunderstandings of the questions or inaccurate self-reporting of nomophobia levels. Due to the cross-sectional design of the study, the authors are unable to establish causal relationships between the variables under investigation.

Conclusion

This study addressed the topic of nomophobia and its correlation with college students’ usage of smartphones and demographic factors. The results suggest that utilizing smartphones for different reasons plays a role in developing students’ anxiety regarding missing out or encountering discomfort. Educators and legislators should consider incorporating teaching on smartphone use and nomophobia into academic curricula to raise awareness of the possible effects of nomophobia on mental and physical health and academic performance. Further studies should explore how students manage when they are unable to use their smartphones.

Relevance for clinical practice

Understanding the prevalence and predictors of nomophobia among university students is crucial for mental health professionals in clinical practice as it allows for more targeted and effective interventions. Several implications arise from this understanding. First, mental health practitioners can raise awareness about nomophobia through educational campaigns and workshops, providing information on the risks of excessive smartphone use and strategies for maintaining a healthy relationship with technology. Second, integrating nomophobia screening tools into mental health assessments can help identify at-risk students early, enabling personalized treatment plans. Third, cognitive-behavioural therapy techniques can be employed to modify maladaptive thoughts and behaviours associated with nomophobia, focusing on anxiety reduction, emotion regulation, and self-control. Lastly, clinicians can assist students in establishing healthy smartphone use guidelines, such as implementing technology breaks, creating ‘tech-free’ zones or times, and promoting alternative leisure activities to reduce nomophobia-related distress and foster a balanced approach to smartphone use. These implications can inform clinical practice and contribute to the overall well-being of university students.

Author contributions

All authors contributed to the study conception and design. Nahla Al Ali and Sara Matarneh performed material preparation, data collection, and analysis. Nahla Al Ali wrote the first draft of the manuscript, and all authors commented on previous versions. All authors read and approved the final manuscript. Nahla Al Ali contributed substantially to conceptualization, methodology, formal analysis, and manuscript writing. Sara Matarneh was responsible for recruitment and data collection and had full access to all the data in the study. Nahla Al Ali and Sara Matarneh were responsible for data analysis, drafting, and critical revisions of the manuscript. Nahla Al Ali takes responsibility for the integrity of the data in the study and the accuracy of the data analysis. All authors contributed to the write-up.

Ethical approval

Approval number 29/132/2020 (research No.284/2020) was obtained from the Institutional Review Board (IRB) for Human Research at the Jordan University of Science and Technology.

Patient consent

Patient consent for publication statement (if relevant) – Not applicable.

Disclosure statement

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

Data availability statement

The datasets generated and analysed during the current study are available from the corresponding author [Dr. Nahla Al Ali] on reasonable request.

Additional information

Funding

No funding was received for conducting this study.