The study included 250 undergraduate students: 38.8% males (97/250) and 61.2% females (153/250) with mean age of 19.7±1.68 years (range 18-29years). The pool of participants included 87 students from school of medicine, 51 from school of dental surgery, 96 from school of nursing and 16 from school of allied sciences.
Most of the participants (224) attended private or boarding schools before joining medical school. 74% (185) of the participants currently resided in hostel. Smartphone was commonly found to be used for communication, social networking, gaming and study purposes (26.8%). 26.8% (67/250) of the participants self-rated themselves as addicted to smartphone, 42% (105/250) did not rate themselves as addicted and the rest 31.2% (78/250) had no opinion of the same. (Table 1)
Table 1. Characteristics of study participants
Variables
|
Frequency (%)
|
Variables
|
Frequency (%)
|
|
Gender
|
|
|
Reasons for using Smartphone
|
|
|
|
Male
|
97
|
(38.8%)
|
Communication
|
16
|
(6.4%)
|
|
Female
|
153 (61.2%)
|
Social networking and gaming
|
23
|
(9.2%)
|
|
|
|
|
Studying
|
12
|
(4.8%)
|
|
Faculty
|
|
|
Communication, social
|
25
|
(10%)
|
|
|
|
|
networking and gaming
|
|
|
|
School of medicine
|
87
|
(34.8%)
|
Social networking, gaming and
|
59
|
(23.6%)
|
|
|
|
|
study purposes
|
|
|
|
School of Dental Surgery
|
51
|
(20.4%)
|
Communication and study
|
48
|
(19.2%)
|
|
School of Nursing
|
96
|
(38.4%)
|
Communication, social
|
67
|
(26.8%)
|
|
|
|
|
networking, gaming and study
|
|
|
|
|
|
|
purposes
|
|
|
|
School of Allied sciences
|
16
|
(6.4%)
|
Self-Perception of Smartphone addiction
|
|
Past Educational Institute
|
|
|
Yes
|
67
|
(26.8%)
|
|
Private/ Boarding School
|
224 (89.6%)
|
Don’t Know
|
78 (31.2%)
|
|
Government/ Public
|
26 (10.4%)
|
No
|
105 (42%)
|
School
|
|
|
|
Place of residence
|
|
Duration of Smartphone use (weekdays)
|
|
Hostel
|
185(74%)
|
>5hours/weekdays
|
42 (16.8%)
|
|
|
|
|
|
|
Day-scholar
|
65(26%)
|
≤5hours/weekdays
|
208(83.2%)
|
|
|
|
|
|
|
Indications of disturbance in daily life was reported by over 60% participants. The study also reported nomophobia among 72.4% of participants. Likewise, phubbing was reported among 37.6 % participants. Overuse was reported by 60.8% participants. Tolerance was observed in 42.8% participants who accepted peoples concern about excessive smartphone use. (Table 2)
Table 2. Prevalence of smartphone addiction (SAS-SV) symptoms among study participants
|
Symptoms
|
Items
|
n (%)
|
|
Disturbance
|
|
I have missed planned work due to Smartphone use.
|
108(43.2)
|
|
in daily life
|
|
I have a hard time concentrating in class, while doing my assignments
|
64(25.6)
|
|
|
|
or while working due to Smartphone use.
|
|
|
|
|
I feel pain in the wrist or on the back of my neck due to smart phone
|
98(39.2)
|
|
|
|
use.
|
|
|
Withdrawal
|
I will not be able to stand not having a Smartphone.
|
142(56.8)
|
|
|
|
I feel impatient and fretful when I am don’t have my Smartphone with
|
109(43.6)
|
|
|
|
me.
|
|
|
|
|
I have Smartphone on my mind even when I am not using it.
|
73(29.2)
|
|
|
|
I will not give up using my Smartphone even when my daily life is
|
36(14.4)
|
|
|
|
already greatly affected by it.
|
|
|
Virtual
|
I constantly check my Smartphone so as not to miss conversation
|
94(37.6)
|
|
relationship
|
between other people on twitter, Facebook, Viber, WeChat, snapchat.
|
|
|
Overuse
|
|
I feel like I am using my Smartphone more than I had intended.
|
152(60.8)
|
|
Tolerance
|
The people around me tell me that I use my Smartphone too much.
|
107(42.8)
|
Smartphone addiction was found among 36.8% (92/250) of the participants with equal numbers of male and females (46). A higher percentage of males were found to be addicted to smartphones (M=47.42% F=30.06%). The average addiction score among males was 30.23±9.40 and that among females was 28.89±8.63. A higher average addiction score was obtained among females.
Participants using smartphone for communication, study, gaming and social networking had the higher addiction scores (40.37±6.04). Participants accepting self-addiction reported highest addiction scores followed by those who used smartphones for longer duration during weekdays. (Table 3)
Table 3. Smartphone addiction (total SAS-SV) and participants’ characteristics
|
Parameters
|
|
Overall SAS-SV
|
Addiction Score
|
|
|
|
score mean± SD (n)
|
mean ±SD (n)
|
|
Gender
|
|
|
|
|
Male
|
|
30.23±9.40 (97)
|
38.21±5.63(46)
|
|
Female
|
|
28.89±8.63 (153)
|
39.36±5.45(46)
|
|
Faculty
|
|
|
|
|
School of Medicine
|
|
30.29±9.23 (87)
|
38.49±5.50(39)
|
|
School of Dental Surgery
|
|
28.66±10.85 (51)
|
40.69±7.10(17)
|
|
School of Nursing
|
|
28.34±7.35 (96)
|
38.10±3.47 (28)
|
|
School of Allied Sciences
|
|
30.62±10.09 (16)
|
38.86±4.54(8)
|
|
Past Educational Institute
|
|
|
|
|
Private/ Boarding School
|
|
29.67±9.17(224)
|
39.06±5.58(85)
|
|
Government/ Public School
|
|
27.15±6.30(26)
|
35.42±3.65(7)
|
|
Reasons for using Smartphone
|
|
|
|
|
Communication
|
|
24.43±5.09(14)
|
33.11±0.63(2)
|
|
Social networking and gaming
|
|
28.34±8.43(23)
|
38.41±3.92(7)
|
|
Studying
|
|
28.91±6.30(12)
|
34±2.99(5)
|
|
Communication, social networking and gaming
|
|
26.44±9.12(25)
|
36.50±5.07(8)
|
|
Social networking, gaming and study purposes
|
|
28.77±9.49(59)
|
38.98±6.54(20)
|
Communication and study
|
29.64±7.85(48)
|
37.77±3.88(18)
|
|
Communication, social networking, gaming and study
|
32.56±9.59(67)
|
40.37±6.04(34)
|
|
purposes
|
|
|
|
Duration of Smartphone use / weekday
|
|
|
|
>5hours
|
32.66±10.04(42)
|
39.72±6.95(23)
|
|
<=5hours
|
28.75±8.58(208)
|
38.46±5.01(69)
|
|
Self-Perception of Smartphone addiction
|
|
|
|
Yes
|
35.55±8.18(67)
|
39.80±6.66(44)
|
|
No
|
25.17±6.87(105)
|
36.86±2.74(15)
|
|
Don’t Know
|
29.85±8.94(78)
|
38.26±4.45(33)
|
|
Residence at present time
|
|
|
|
Hostellers
|
28.81±8.80(185)
|
38.89±5.18(32)
|
|
Day-scholars
|
31.92±9.20(65)
|
38.72±5.79(60)
|
|
Among 92 smartphone addicted participants, 44 (65.7%) had self-rated themselves positively for addiction. 15(14.3%) participants who did not self-accept were found to be addicted, and 33 (42.3%) of those who did not opine were addicted to smartphone. Smartphone addiction was found to be associated with gender, duration of use and self-acceptance of smartphone addiction. It was not associated with faculty, past educational institute and place of residence at current time. (Table 4)
Table 4. Association between smartphone addiction and participants’ characteristics
|
Variable
|
|
|
Addiction
|
χ2
|
|
p-
|
|
|
|
Addicted
|
|
Not-addicted
|
|
|
value
|
|
|
|
n
|
|
n
|
|
|
|
|
Gender
|
|
|
|
7.690
|
0.006
|
|
Male
|
|
46
|
|
51
|
|
|
|
|
Female
|
46
|
|
107
|
|
|
|
|
Faculty
|
|
|
|
|
6.278
|
|
0.099
|
|
School of Medicine
|
39
|
|
48
|
|
|
|
|
School of Dental Surgery
|
|
17
|
|
34
|
|
|
|
|
School of Nursing
|
28
|
|
68
|
|
|
|
|
School of Allied Sciences
|
|
8
|
|
8
|
|
|
|
|
Past Educational Institute
|
|
|
|
1.217
|
0.270
|
|
Private/ Boarding School
|
|
85
|
|
139
|
|
|
|
|
Government/ Public School
|
7
|
|
19
|
|
|
|
Duration of Smartphone use / weekday
|
|
|
7.003
|
0.008
|
|
>5hours
|
23
|
19
|
|
|
|
<=5hours
|
69
|
139
|
|
|
|
Self-Perception of Smartphone addiction
|
|
|
47.915
|
<0.001
|
|
Yes
|
44
|
23
|
|
|
|
No
|
15
|
90
|
|
|
|
Don’t Know
|
33
|
45
|
|
|
|
Residence at present time
|
|
|
41.145
|
0.420
|
|
Hostellers
|
32
|
153
|
|
|
|
Day-scholars
|
60
|
5
|
|
|
|
Male undergraduate medical students were more likely to be addicted than females (OR: 1.99). Self-acceptance of addiction was the biggest predictor of smartphone addiction among the studied variable. (OR: 11.088) (Table 5)
Table5. Multiple Logistic Regression between smartphone-use variables and addiction
Variable
|
B
|
p-value
|
OR
|
95% CI
|
Gender
|
Male
|
0.688
|
0.027
|
1.990
|
1.082-3.65
|
Female
|
|
|
1
|
|
Duration of Smartphone use / weekday
|
>5hours
|
0.157
|
0.690
|
1.17
|
0.541-2.531
|
<=5hours
|
|
1
|
|
Self-Perception of Smartphone addiction
|
Yes
|
2.406
|
<0.001
|
11.088
|
5.715-24.039
|
Don’t know
|
1.331
|
|
3.786
|
1.835-7.814
|
No
|
|
1
|
|