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ORIGINAL ARTICLE
Year : 2023 | Volume
: 67
| Issue : 1 | Page : 15-20
Smartphone addiction in medical students: Association with perceived stress, personality factors and loneliness
Nitisha Verma, Haseeb Khan, Astha Singh, Rakesh Saxena
Assistant Professor, Department of Psychiatry, Hind Institute of Medical Sciences, Barabanki, Uttar Pradesh, India
Correspondence Address:
Nitisha Verma
B-506, Prateek Laurel Apartment, Sector 120, Noida, Gautam Buddha Nagar, Uttar Pradesh
India
Source of Support: None, Conflict of Interest: None
CheckDOI: 10.4103/ijph.ijph_10_22
Abstract
Background: Smartphone addiction (SMA) is an emerging concept. It has been associated with high perceived stress. There is a dearth of data on its association with loneliness and personality in the Indian context. Objectives: We planned this study to estimate the prevalence of SMA in medical students, verify its reported association with perceived stress, and determine its association with personality factors and loneliness. Methods: Four hundred and two medical students participated in this cross-sectional study. We used the SMA scale-short version to divide students into those having an addiction and not having an addiction. The Perceived Stress Scale, ten-item personality inventory, and University of California, Los Angeles Loneliness Scale were used to assess perceived stress, personality, and loneliness. Ninety-five percent confidence intervals were reported for all comparisons. Results: The prevalence of SMA in medical students was 34.8%. SMA was associated with higher perceived stress and loneliness. Students having SMA scored lower on personality domains of extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience. Moreover, SMA interfered with students' social life and academic performance. Conclusions: SMA is a cause for concern. We need to plan the awareness campaigns focusing on SMA and its association with social life and academic performance. Researchers need to explore this concept in larger samples and diverse population groups to know its actual magnitude and impact. Moreover, dedicated psychiatric committees need to recommend the guidelines for the judicious use of smartphones.
Keywords: Loneliness, personality, smartphone, stress
Introduction 
The 21st century witnessed many technological advancements including the Internet and smartphones. Increasing use and dependence on the Internet became a cause for concern and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) proposed a new diagnostic entity “Internet Gaming Disorder” under the conditions for further study.[1]
Similarly, the concept of “problematic smartphone use” and “smartphone addiction (SMA)” emerged with an increase in the use of smartphones. The “SMA scale” was developed for the quantification of smartphone use.[2]
A meta-analysis of 19 studies comprising 5497 Asian medical students reported the prevalence of SMA as 41.93%.[3] Recent Indian studies have found the prevalence of SMA to range from 36% to 46.15% in medical students.[4],[5],[6],[7] SMA has been associated with stress, anxiety, depression, neuroticism, poor sleep quality, fatigue, accidents, and poor academic performance in students.[3],[5],[7],[8],[9]
However, literature has contrasting views regarding its association with personality factors and loneliness.[10],[11],[12] Furthermore, there is a dearth of data on this aspect in the Indian settings.
Hence, we planned this study to understand more about SMA among medical students. Our objectives were to estimate the prevalence of SMA in medical students, verify its reported association with perceived stress, and determine its association with personality factors and loneliness.
Materials and Methods A cross-sectional study was conducted at a medical college in North India. Approval was obtained from the Institutional Ethics Committee and informed consent was obtained from participants. Undergraduate students, between 18 and 25 years of age, using smartphones for at least 1 year were included in the study. Students not willing to give informed consent were excluded. One-year duration was mentioned in the inclusion criteria as DSM-5 mentions 1 year of clinically significant impairment or distress for the diagnosis of all addictive disorders, including the “Internet Gaming Disorder.”[1]
All students fulfilling the eligibility criteria were included. Data were collected using the Google forms. The link for Google forms was shared on the WhatsApp group of all five batches of students (MBBS I, II, III, IV, and interns). Google forms comprised separate sections for analyzing each variable. Any information, which could reveal the identity of respondents was not asked in the Google forms to maintain confidentiality. Brief information regarding the nature and purpose of the study, scales, and how to fill in the responses was also shared along with contact details of the principal investigator so that the participants may ask their queries.
Data were collected over 20 days in February 2020. CDC OpenEpi software was used to calculate the sample size.[13] Taking the anticipated frequency as 36.4,[7] within 5% confidence limits and 95% confidence level, the sample size was calculated as 356. Adjusting for the expected response proportion of 90%, the sample size came out to be 395.55.
Tools used
Semi-structured pro forma
Comprised questions related to sociodemographic variables and patterns of smartphone use. These questions were taken from similar recent Indian studies.[4],[5] Due permission was obtained from the authors.
Smartphone addiction scale short version (SAS-SV)
A self-administered ten-item 6-point Likert scale with Cronbach's alpha of 0.91 and good concurrent validity with the SMA scale. Cutoff values are 31 for males and 33 for females[2]
Ten item personality inventory
A self-report ten-item 7-point Likert scale with Cronbach's alpha of 0.66 and test-retest reliability of 0.72. It measures personality traits related to the big five personality factors: Extraversion, agreeableness, conscientiousness, emotional stability (ES), and openness to experience (OE).[14]
Perceived stress scale-10 item
A self-administered ten-item 5-point Likert scale having a good convergent validity and reliability (Cronbach's alpha 0.89). It assesses participants' subjective perception of stress during the previous month. The score ranges from 0 to 40 with higher scores indicating higher stress.[15],[16]
University of California, Los Angeles Loneliness Scale
A six-item 4-point Likert scale with Cronbach alpha of 0.82. It measures one's subjective feelings of loneliness and feelings of social isolation.[17]
Procedure
Participants were divided into two groups: Those having SMA and not having SMA depending on their scores on the SMA scale short version (SAS-SV). The groups were then compared using appropriate statistical tests to determine the association between SMA and other variables.
Data analysis
IBM SPSS version 20 statistical software was used for the statistical analysis. The Shapiro–Wilk's test for normality revealed that the data were normally distributed. (refer [Supplementary Table]) Descriptive statistics were used to analyze the responses to the semi-structured questionnaire. The Chi-square test was used to compare the study groups on socio-demographic variables and smartphone use patterns. The independent t-test was used to compare them on perceived stress, personality factors, and loneliness. Statistical significance was considered at P < 0.05. We also calculated 95% Confidence intervals (CI) for the comparisons.
Results Four hundred and two out of 447 students filled in the responses (response rate: 89.9%). No specific reasons were cited in the Google forms by the 45 students who declined participation. As we did not gather any information which could reveal their identity, we were unable to trace them and explore the reasons behind their decision.
There were 191 males (47.5%) and 211 females (52.5%). The mean age of students was 22.4 ± 2.2. Most students reported using smartphones for 2–6 h a day (259 of 402 students, 64.4%), 105 (26.1%) reported using smartphones for more than 6 h a day. Only 38 students (9.5%) used smartphones for <2 h a day. Smartphones were most commonly used for social networking (170; 42.3%), followed by entertainment (124; 30.8%) and educational purposes (108; 26.9%).
Prevalence
One hundred and forty out of four hundred and two students had SMA (34.8%; 95% CI: 30.2–39.7).
Eighty-three of 191 males and 57 of 211 females had SMA. We found that the prevalence was more in males (43.5% [95% CI: 36.3–50.8]) as compared to females (27% [95% CI: 21.2–33.5]). This gender difference was statistically significant (odd's ratio: 2.08 (95% CI: 1.37–3.15); Chi-square statistics: 11.98, P = 0.001).
Furthermore, we obtained a statistically significant difference in the responses between the two groups [Table 1].
Association of smartphone addiction with personality factors, perceived stress, and loneliness
We found that students having SMA scored lower on the personality domains of extraversion, agreeableness, conscientiousness, ES, and OE, as compared to those not having SMA. This difference was statistically significant for all domains except extraversion.
However, even for extraversion, 95% CI reveals that the results were more compatible with a lower score for students having SMA.
Students having SMA also scored significantly higher on the perceived stress scale (PSS-10) and University of California, Los Angeles (UCLA) Loneliness scale [Table 2].
Table 2: Comparison of personality factors, Perceived Stress Scale and University of California, Los Angeles Loneliness Scale scoresPearson's correlation between smartphone addiction and other variables
We found a negative correlation between SMA and personality domains of extraversion, agreeableness, conscientiousness, ES, and OE, although this correlation was statistically significant for all except extraversion.
We also found a statistically significant positive correlation between SMA and perceived stress and loneliness [Table 3].
Table 3: Pearson's correlation between smartphone addiction and other variables Discussion The prevalence of SMA among medical students was 34.8%. A similar Indian study found the prevalence as 36.4%.[7] Other studies have reported it as 44.7% and 46.2%.[5],[6] This difference across the studies could be due to the differences in the sociodemographic characteristics of students.
We also found that SMA was more prevalent in males as compared to females. This finding was similar to that reported by Lei et al. who studied SMA in 574 medical students and found the prevalence to be higher in males (49.2% vs. 36.6%).[18]
Literature has equivocal views about gender and SMA. Some studies have reported that SMA is more common in females while others have reported no significant gender difference.[5],[7],[19],[20] Gender differences could be due to different motives behind using smartphones. Males use smartphones more for entertainment, like playing games whereas females use them more for social interactions.[21] Motives behind smartphone use and associated gender differences were not assessed as they were beyond the scope of our study.
Students having SMA were more likely to check their phones before going to sleep and at night if they get up from sleep as compared to students not having SMA. They also reported more distress when they forget their phone elsewhere. Similar findings have been reported in the literature.[5] Furthermore, smartphone use had significantly interfered with students' social life and academic performance.
The National Mental Health Survey (NMHS) 2016 found the current prevalence of any mental morbidity as 10.56%. The maximum prevalence was for substance use disorders.[22] In our study, the prevalence of SMA was higher than that reported for any disorder in the NMHS 2016. Moreover, impairment in social life and occupational functioning is one of the key diagnostic criteria for any disorder in the DSM-5.[1]
SMA is a major cause for concern for both students and clinicians. Students need to be made aware of the addictive potential of smartphones so that they could use them for their benefit and not fall prey to their habit-forming potential. Furthermore, clinicians need to keep this in mind while evaluating students for poor academic and social functioning.
We found that students who had SMA had higher stress as compared to those who did not have SMA. Similar findings have been reported in the literature.[5],[23] Elevated levels of stress have been reported in medical students due to academic burden, frequency of examinations, lengthy academic curriculum, etc. Stress may lead to negative emotions and smartphones may be used as a passive coping mechanism to deal with negative emotions. Smartphones have various applications and functions which can be easily accessed to seek pleasure and ease stress.[23],[24] Thus, smartphone use may get negatively reinforced and transform from harmless to addictive behavior.
On the other hand, spending too much time on smartphones may adversely affect their academic performance [Results section; [Table 1]: question 5] and lead to increased levels of stress.
Using similar tools as ours, Dharmadhikari et al. studied 195 medical students in Maharashtra and found a statistically significant positive correlation between perceived stress and SMA.[5] Wang et al. assessed 769 medical students in China on Mobile Phone Addiction Index Scale and PSS (14 items). Although they used a different tool for assessing SMA, they also reported similar findings.[23]
Furthermore, students who had SMA also scored higher on the loneliness scale. This is in line with other studies which have reported higher loneliness scores in students having SMA.[12],[25] We conducted this study on medical students, most of whom stayed in hostels away from their homes. Many of them were from different states of the country. Feeling lonely, they may have resorted to smartphone use to combat their feelings of loneliness.[26],[27] Negative reinforcement might have turned this harmless smartphone use into a repetitive addictive behavior.
On the other hand, excessive use of smartphones may result in decreased social and interpersonal interaction [Results section; [Table 1]: point 4]. Spending less time with family and friends may lead to feelings of loneliness.[12]
Singh and Kumari assessed 120 college students in North India on the SMA Scale (33 items) and Perceived Loneliness Scale (36 items). They found a positive relationship between SMA and loneliness.[25] Sönmez et al. studied 682 nursing students in Turkey. They used SAS-SV and UCLA Loneliness scale (20 items) and found a positive correlation between loneliness and SMA.[12] Jiang et al. assessed 438 international students in China on SAS-SV and UCLA Loneliness scale (10 items). They found loneliness as a strong predictor of SMA.[27] Aktürk et al. assessed 1156 high school and university Turkish students on SAS-SV and Short Loneliness scale. However, they found no relation between loneliness and SMA.[10] This difference in findings could be due to the difference in the sociodemographic characteristics of participants. While Aktürk assessed high school and university students, others studied only college students. High school students mostly stay with their parents, whereas college students mostly stay away from home. Staying with parents could have provided social support and prevented students from feeling lonely. We also conducted this study on college students and found that loneliness was correlated with SMA.
Although we found a statistically significant positive correlation between SMA and perceived stress and loneliness, the causal relationship between these variables could not be established and may be ascertained by future longitudinal studies.
Students having SMA scored lower on personality domains of extraversion, agreeableness, conscientiousness, ES, and OE. Furthermore, a statistically significant negative correlation was obtained between SMA and all domains except extraversion. Similar results have been reported by Erdem and Uzun. They studied 494 undergraduate students on the SMA scale (33 items) and big-five inventory (10 items). Agreeableness, conscientiousness, and OE were negatively correlated and neuroticism was positively correlated with SMA in their study.[28] Eichenberg et al. assessed 497 university students in Vienna on SMA Scale by Biang and Leung (19 items) and big-five inventory (10 items). They also found that students with problematic smartphone use had higher scores on neuroticism.[26] Furthermore, Prasad et al. reported a negative correlation between the use of social networking apps and conscientiousness, OE.[7]
ES is the tendency to be stable and calm. It is the opposite of neuroticism, which is the tendency to experience negative emotions such as anxiety, worries, and instability.[29] Individuals low on the ES domain are more likely to experience negative emotions and may end up using smartphones as a source of experiencing pleasure. Smartphone use may thereby get negatively reinforced and transform from a harmless behavior to an addictive behavior. Consistent findings supporting negative reinforcement of smartphone use to alleviate negative emotions such as stress and loneliness have been obtained on all three scales used in our study. Literature has also reported neuroticism to be a strong positive predictor of SMA.[28]
Agreeableness is the tendency of being sympathetic, generous, forgiving, kind, and considerate. Agreeable individuals are more cooperative in their behaviors whereas individuals low on agreeableness are less pleasant in their social relations and may also be uncooperative or argumentative in their dealing with others.[29] Individuals low on agreeableness may not have many social contacts due to their uncooperative/argumentative nature and hence may have more time available to use smartphones. Furthermore, less agreeable individuals might use smartphones to make up for the loss of social contacts.
Conscientiousness is the ability to have self-discipline and control. Individuals high on conscientiousness are efficient, dependable, organized, responsible, well-planned, monitor their behavior cautiously, and conform to rules.[29] These traits make individuals high on conscientiousness less likely to have SMA.
OE is the tendency to be adventurous, creative, curious, and willing to explore new situations. Individuals scoring high in this domain have a wide range of interests and prefer variety.[29] These traits make them more likely to explore situations in real life rather than restricting themselves to smartphone use.
Extraversion is the tendency of being social, outgoing, talkative, enthusiastic, and energetic. Extrovert people maintain friendships and value their interpersonal relationships. On the other hand, individuals low on extraversion are introverts. They prefer to maintain distance from others.[28] As introvert students prefer to remain distant from others, they might get more time for using smartphones. Smartphone use could also be a means of seeking pleasure and getting relief from negative emotions as these students do not have many social contacts to rely on in times of need, thereby making them vulnerable to SMA. On the other hand, extrovert students prefer to maintain friendships in the real life and have less time to spend on smartphones.
These findings highlight the importance of personality traits in SMA and may be used for screening individuals at risk for SMA. It also guides therapists in planning psychotherapeutic interventions for individuals having SMA.
Limitations
The findings of our study could only be generalized to medical students between 18 and 25 years of age. Social desirability bias may have affected the responses as those were self-rated. Moreover, as we did not gather any information which could reveal the identity of our participants, we were unable to trace those who denied participation and explore the reasons behind their decision. They might have scored higher on the SAS-SV. Both the above statements might have made the actual prevalence of SMA even higher than what we found in our study.
The cause-and-effect relationship could not be ascertained due to the cross-sectional design of our study.
Panova and Carbonell argued that as smartphones are used to access the Internet, addiction is with the Internet and not with smartphones. They have also proposed that using the Internet, social networking, gaming, etc., should be explored in the context of their motivations, gratifications, and sociocultural context and not as components of SMA.[30] We have not distinguished between SMA and Internet addiction in our study, as it was beyond its scope. Future studies assessing both SMA and Internet addiction in the same group of subjects could give a better understanding of this aspect.
Implications and future directions
Despite certain limitations, our study adds to the available literature, especially in the Indian context. It verifies the reported association between SMA and higher stress in medical students. Furthermore, our study has tried to establish an association between SMA and loneliness and the big-five personality traits. The implications of these associations have also been discussed. SMA has become a cause for concern for students, parents, and clinicians alike. Awareness campaigns for students highlighting SMA, and its association with social life and academic performance will be beneficial in decreasing its magnitude and impact.
Researchers need to study this topic further in larger samples and diverse population groups to know its actual magnitude and impact. Furthermore, several factors and clinical indicators leading to SMA need to be explored. Dedicated psychiatric committees at national and regional levels need to be vigilant about this emerging behavioral addiction and recommend guidelines for the judicious use of smartphones. They also need to formulate the recommendations for the management of SMA.
Conclusions The prevalence of SMA among medical students is 34.8%. SMA is associated with higher levels of perceived stress and loneliness. Students having SMA score significantly lower on the big-five personality domains of ES, agreeableness, conscientiousness, and OE.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References 
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