143© 2021 Medical Journal of Dr. D.Y. Patil Vidyapeeth | Published by Wolters Kluwer - Medknow
Aim: The aim of this study was to assess the prevalence of Internet addiction (IA) and its correlation with personality traits and perceived parenting styles in college‑going students. Materials and Methods: The current cross‑sectional study was done at a medical college in a semi‑urban area near Pune. A total of 623 university students were included in the study with their consent. They completed a questionnaire assessing sociodemographic background and Internet usage pattern, Young’s IA scale to assess IA, the Big Five Inventory for assessing personality traits, and Short‑Form Egna Minnenav Barndoms Uppfostran (My Memories of Upbringing) scale for measuring perceived parenting styles. Results: The prevalence of IA in medical students was 56.81% (mild IA: 49.59%, moderate IA: 7.22%). Neuroticism showed a significant positive correlation with IA, whereas extroversion, openness to experience, agreeableness, and conscientiousness showed a significant negative correlation. In perceived parenting styles, rejection and overprotection had a significant positive relation and emotional warmth had a significant negative relation with IA. Conclusion: Neuroticism, rejection, and overprotection by parents were positively associated with IA. Personality traits of extroversion, openness to experience, agreeableness, conscientiousness, and emotional warmth by parents were negatively associated with IA.
Keywords: Addiction, extroversion, medical students, neuroticism, parenting, prevalence
Parenting Style and Personality Correlates of Internet Addiction: A Cross‑Sectional StudySunil Shivam, Bhushan Chaudhari, Suprakash Chaudhury, Daniel Saldanha
Access this article onlineQuick Response Code:
Website: www.mjdrdypv.org
DOI: 10.4103/mjdrdypu.mjdrdypu_329_19
Address for correspondence: Dr. Suprakash Chaudhury, Department of Psychiatry, Dr. D Y Patil Medical College, Dr. D Y
Patil Vidyapeeth, Pimpri, Pune ‑ 411 018, Maharashtra, India. E‑mail: [email protected]
may end up becoming “Internet addiction (IA)” defined as "An individual’s inability to control his or her own use of Internet causing disturbances and impairment in fulfillment of work, social and personal commitments; and … shares similarities with other categories of behavioral addictions and substance use".[2] Addiction to the Internet may lead to a loss in productivity, health, and interrelation problems.[3,4] College‑going students may lose essential time with pathological Internet use and experience a steady decline in academic and social performance leading to occupational incompetence.[5,6]
Original Article
Introduction
The Internet, which is widely used globally, has both positive and negative influences on human
life. Since coming into existence in the 1960s, the Internet has now become the backbone of modern society. The use of the Internet is rapidly increasing, with technology becoming cheaper and accessible. Even low‑ and middle‑income countries are showing a significant rise in Internet users. India has had an exponential rise in Internet users over the last decade, with four hundred million (36.5% of the population) active Internet users.[1] An increase in the use of the Internet and reliance on it for work, study, and leisure activity has led to its constant presence in life. Due to the fundamental nature of the Internet being a tool for work, it is harder to form boundaries between functional and dysfunctional uses. Dysfunctional use of the Internet
Department of Psychiatry, Dr. D Y Patil Medical College, Dr. D Y Patil Vidyapeeth, Pimpri, Pune, Maharashtra, India
This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution‑NonCommercial‑ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non‑commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
For reprints contact: [email protected]
How to cite this article: Shivam S, Chaudhari B, Chaudhury S, Saldanha D. Parenting style and personality correlates of internet addiction: A cross-sectional study. Med J DY Patil Vidyapeeth 2021;14:143-54.
Abs
trac
t
Submission: 29‑11‑2019,Decision: 08‑05‑2020, Acceptance: 27‑05‑2020, Web Publication: 12-02-2021
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
144 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
Personality not only defines the individuals’ behavioral style but also represents the relatively enduring characteristics of individuals, and it refers to all aspects of individuality. Human activities and types of behavior are consistent with specific traits of personality. The research literature on personality factors and Internet usage has been growing.[7‑9] As personality remains consistent over the life span and different situations, it is found to influence the propensity to behavior addictions.[10-12] In recent years, the use of the Internet has expanded to individuals from every walk of life. Since the usage pattern of the Internet is very discrete, personality might be playing a key role in predisposing individuals to this behavioral addiction. The Big Five model is regarded by general consensus as a unified framework for personality trait.[13,14] Structure and integrity of the Big Five construct of personality has been verified by many studies in different settings.[15,16] This led us to choose this model for our study.
Psychosocial development and development of personality depend on a certain element of family life which includes parenting style and attitude of parents toward children. In the debate of nature versus nurture despite a conflict, everyone agrees that the family environment plays a major role in the development of an individual. Conflicts among family members, broken homes, and overindulgence by parents have been associated with various addictions and adverse psychosocial outcomes of individuals in the future.[17] Behavioral addiction such as IA may be a manifestation of individuals, in whom the attitude of their parents and familial environment acts as a predisposing factor.[18] As most of our study sample stay away from home, we measured the perception of parenting among them. Unavailability of any research study in India comparing personality traits and parenting rearing style led us to undertake this research work to assess parenting styles and personality correlates of IA.
Materials and MethodsThis cross‑sectional analytical study was conducted in a medical college in a semi‑urban area of Maharashtra during the period September 2017 to September 2019. Dr. DY Patil Medical College Ethics Committee clearance was obtained (letter no. DPU/R&R (M)/31/(83)/2018 dated January 12, 2018) before the start of the study. Ethical principles were clearly explained to the participants, especially voluntary nature of their participation and option of withdrawal from the study at any time. Following this, informed consent was taken.
SampleMedical students both undergraduate and postgraduate fulfilling the inclusion and exclusion criteria of the study were selected by purposive sampling.
Inclusion criteriaStudents who had been using the Internet for at least 6 months before the study and who gave consent to the study were included.
Exclusion criteriaStudents not using the Internet were excluded.
Sample size calculationIn the community‑based studies, 10%–20% allowable error is accepted.
Formula used in calculating sample size is:
n = (4pq)/(L2).
where P is previous prevalence which is P = 15%
L = allowable error = 20% = 20% of prevalence = 20% of 15 = 3
q = 1 − P = 1–0.15 = 0.85.
n = 4 × 0.85 × 0.15/0.03 × 0.03 = 567–600.
Tools usedQuestionnaire about demographic details and Internet useInformation about age, sex, parents’ education, Internet connection and speed, usage of social media, E‑mail, online gaming, and music and video streaming was obtained.
Internet addiction testInternet addiction test (IAT) is a self‑rated scale developed for measuring the level of IA and has been used extensively for this purpose. It contains 20 questions to be scored on a Likert scale from 1 (rarely) to 5 (always). A total score of <20 represents normal user, between 20 and 49 represents mild addiction, between 50 and 79 represents moderate addiction, and between 80 and 100 represents severe addiction.[19] The IAT had a Cronbach’s alpha coefficient of 0.91. The internal consistency score for the first, second, third, or fourth factor was 0.76, 0.74, 0.69, or 0.63, respectively. An exploratory factor analysis with 256 university students showed four factors with eigenvalues more than 1. These four factors explained 56.5% of the total variance.[20]
The Big Five InventoryThis 44‑item measure yields a score for each of the Big Five personality factors. Each item consists of a short statement, and respondents are required to rate the degree
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
145Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
to which they agree with each statement on a 5‑point Likert scale (1 = “strongly disagree” to 5 = “strongly agree”). It provides reliable and valid data.[21‑24] Cronbach’s alpha of the Big Five Inventory factors ranged from 0.65 to 0.81 (Mdn = 0.79). The factor analyses identified the five factors associated with the FFM.[24]
Short‑Form Egna Minnenav Barndoms Uppfostran (My Memories of Upbringing)This Swedish self‑report scale assesses one’s memory of parental rearing and consists of four replicable dimensions: rejection, emotional warmth, overprotection, and favoritism. Responses are rated on a 4‑point Likert scale (0 never; 4 always).[25]
Internal consistency reliability coefficients (Cronbach’s alpha) were all above 0.70. Using the multiple group method, structure matrix and sum of squared factor loadings for each factor by nation were calculated. The strength of each factor exceeded the minimum required value of (1/23) × 100% or 4.35. The factors of the scale had factor strengths that were highly comparable across national samples. Thus, the Short‑Form Egna Minnenav Barndoms Uppfostran measuring constructs had cross‑national factorial invariance.[26]
MethodologyMedical students from 2nd, 3rd, and 4th academic years, interns, and postgraduate students were enrolled for the study. A required number of participants were selected by purposive sampling method from each year of study so that each academic year would have similar representation in the study sample. Written informed consent was taken from each participant, assuring them anonymity of the study to avoid reporting bias. A questionnaire was distributed before the lecture with proper instructions to undergraduate students and during posting hours to interns and postgraduate students. It took 15 min on average to complete the questionnaire. Scoring of the different scales was done manually as per the test manual.
Statistical analysisThe data were analyzed by SPSS software (SPSS, IBM, Chicago, USA). Descriptive statistics were presented in the form of mean, standard deviation, percentage, etc., In inferential statistics, the analysis was done using nonparametric tests, Chi‑square test, Spearman’s rho test, Kruskal–Wallis test, and Mann–Whitney U‑test at 5% significance. A hierarchical linear regression model was constructed. In this model, IA scores were used as the dependent variable. Age, gender, Internet use frequency, and duration, the personality variables (i.e., extraversion, agreeableness, conscientiousness, neuroticism, and openness), and parenting styles (rejection, warmth, and overprotectiveness) were entered into the model as predictors.
ResultsA total of 840 participants were included, of which 623 completed the given questionnaire. The sociodemographic characteristics of the students are shown in Table 1. Of all the students, maximum representation was from 2nd, 3rd, and 4th‑year MBBS students, whereas the completed survey returned by the students doing internship and postgraduate studies was less in comparison. As the reach of the Internet is growing day by day in our society, the age at which the Internet first used is decreasing day by day. Our data show maximum number of students started using the Internet by the age of 13, but the trend is going toward a lower age [Figure 1]. The characteristics of Internet use are given in Table 2. Majority of the students use their mobile phones to access the Internet, mainly in their rooms, use high‑speed Internet, for 1–2 h daily. The usage pattern of the Internet and comparison of usage pattern by gender is given in Table 3. Using the IAT, the prevalence of IA in our population was 56.81%, of which 49.59% had mild IA whereas 7.22% of the students had moderate IA. No case of severe IA was detected in the current study [Table 4].
Association of IA with personality factors and domain of perceived parenting styleConscientiousnessConscientiousness score of students without IA was significantly higher than students with mild IA, and students with mild IA had significantly higher
Table 1: Demographic characteristics of medical students (n=623) included in the study
Characteristics n (%)Gender
Male 240 (38.5)Female 383 (61.5)
Students’ courseSecond year 151 (24.2)Third year 156 (25.0)Fourth year 158 (25.4)Internship 74 (11.9)Postgraduates 84 (13.5)
Place of stayHome 36 (5.8)Private accommodation 194 (31.1)Hostel 393 (63.1)
Father’s educationGraduate 254 (40.8)Postgraduate 369 (59.2)
Mother’s educationHigh school 118 (18.9)Graduate 272 (43.7)Postgraduate 233 (37.4)
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
146 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
conscientiousness and IA was observed (rs (8) = −0.484, P < 0.001) [Table 6].
AgreeablenessAgreeableness score of students without IA was significantly higher than students with mild IA, and students with mild IA had significantly higher scores than moderate IA [Table 5]. A strong and statistically significant, negative correlation between agreeableness and IA was observed (Spearman’s rho = −0.604, P < 0.001) [Table 6].
ExtraversionExtraversion score of students without IA was significantly higher than students with mild IA, and students with mild IA had significantly higher scores than moderate IA [Table 5]. A strong and statistically significant, negative correlation between extraversion and IA was observed (Spearman’s rho = −0.627, P < 0.001) [Table 6].
NeuroticismNeuroticism score of students without IA was significantly lower than students with mild IA, and students with mild IA had significantly lower scores than moderate IA [Table 5]. A strong and statistically significant, positive correlation between neuroticism and IA was observed (Spearman’s rho = 0.752, P < 0.001) [Table 6].
Openness to experienceOpenness to experience score of students without IA was significantly higher than students with mild IA, and students with mild IA had significantly higher scores than moderate IA [Table 5]. A strong and statistically significant, negative correlation between openness and IA was observed (Spearman’s rho = −0.526, P < 0.001).
RejectionRejection score of students without IA was significantly lower than students with mild IA, and students with mild IA had significantly lower scores than moderate IA [Table 5]. A statistically significant, positive correlation between rejection and IA was observed (Spearman’s rho = 0.558, P < 0.001) [Table 6].
Table 3: Usage pattern of Internet among medical studentsEntire sample (n=623) I. Male (n=240) II. Female (n=383) I versus II
Chi‑square testP
Rarely Often Rarely Often Rarely OftenNews sites 70 (11.2) 553 (88.8) 22 (9.2) 218 (90.8) 48 (12.6) 335 (87.4) 1.67 >0.05Video 118 (25.4) 465 (74.6) 83 (34.6) 157 (65.4) 97 (25.3) 286 (74.6) 6.15 <0.05Music 173 (27.8) 450 (72.2) 86 (35.8) 154 (64.1) 84 (35.8) 299 (78.1) 14.3 <0.05Search engine 197 (31.6) 426 (68.4) 58 (24.2) 182 (75.8) 102 (26.6) 281 (73.4) 0.469 >0.05Social network 201 (32.3) 422 (67.7) 68 (28.3) 172 (71.7) 151 (39.4) 232 (60.5) 7.96 <0.05Online games 211 (33.9) 412 (66.1) 50 (20.9) 190 (79.1) 200 (52.3) 183 (47.7) 60.4 <0.05Email 220 (35.3) 403 (64.7) 65 (27.1) 175 (72.9) 163 (42.5) 220 (57.5) 15.2 <0.05
Table 2: Characteristics of Internet use in medical students (n=623)
Characteristics of Internet use n (%)Began Internet use at age of
7 3 (0.5)8 45 (7.2)9 70 (11.2)10 93 (14.9)11 79 (12.7)12 96 (15.4)13 133 (21.3)14 75 (12.0)15 24 (3.9)16 5 (0.8)
Predominant mode of accessDesktop 65 (10.4)Laptop 111 (17.8)Mobile 447 (71.7)
Mode of connection to InternetBroadband 229 (36.1)Mobile Internet 394 (63.1)
Place of maximum Internet useResidence 483 (77.5)Public place 75 (12.0)College 65 (10.4)
Speed of Internet connectionIntermediate 38 (6.1)Fast 585 (93.9)
Time of Internet useDay 322 (51.7)Night 301 (48.3)
Duration of Internet use (h)One 269 (43.2)Two 253 (40.6)Three 65 (10.4)Four 36 (5.8)
Internet addiction scoreNormal 269 (43.17)Mild 309 (49.59)Moderate 45 (7.22)Severe 0 (0)
scores than moderate IA [Table 5]. A strong and statistically significant, negative correlation between
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
147Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
Emotional warmthEmotional warmth score of students without IA was significantly higher than students with mild IA, and students with mild IA had significantly higher scores than moderate IA [Table 5]. A statistically significant, negative correlation between emotional warmth and IA was observed (Spearman’s rho = −0.588, P < 0.001) [Table 6].
OverprotectionOverprotection score of students without IA was significantly lower than students with mild IA, and students with mild IA had significantly lower scores than moderate IA [Table 5]. A statistically significant, positive correlation between overprotection and IA was observed (Spearman’s rho = 0.520, P < 0.001) [Table 6].
Summary of hierarchical regression modelIn the model summary table [Table 7], the multiple regression coefficient “R” measures the standard of the prediction of the dependent variable, i.e., IA. A value of 0.800, within the present study, indicates a good level of prediction. The coefficient of determination or “R Square” in our study was 0.639 which means that our independent variables explain 63.9% of the variability of our dependent variable. The analysis of variance table [Table 8] indicates that within the present study, the independent variables statistically significantly predict the dependent variable (IA), F (12, 610) = 35.875, P < 0.0005 (i.e., the regression model may be a good fit of the data). Unstandardized coefficients indicate what proportion of the dependent variable varies
with an independent variable when all other independent variables are held constant. Consider the effect of age in the present study. The unstandardized coefficient, B1, for age is − 0.088 [Table 9]. This indicates that for each 1‑year increase in age, there is a decrease in IAT score of 0.088. A multiple regression was run to predict IA from gender, age, duration of Internet use, number of times the Internet is accessed, extraversion, agreeableness, conscientiousness, neuroticism, openness, rejection, warmth, and overprotection. These variables statistically significantly predicted IA, F (12, 610) = 35.875, P < 0.0005, R2 = 0.639. Six variables (extraversion, agreeableness, conscientiousness, neuroticism, openness, and rejection) added statistically significantly to the prediction, P < 0.05.
DiscussionThe purpose of this study was to investigate the prevalence and determinants of IA in vulnerable young medical students of a medical college in a semi‑urban area of western Maharashtra. Of 840 questionnaires that were distributed, 623 questionnaires were returned in a fully completed form. The response rate was 74.17% which can be considered good, bearing in mind the fact that participation in the study was voluntary and no incentives were given to study participants.
Of the total study sample, 38.5% were males and 61.5% were females. This was above the national ratio of male to female medical students, with the female being 51.6%, according to a survey conducted in the year 2016 which
Table 4: Prevalence of Internet addictionInternet addiction
Total sample (n=623), n (%)
I. Female (n=383), n (%)
II. Male (n=240), n (%)
I versus II Chi‑square test
Addicted 354 (56.8) 224 (58.4) 130 (54.1) χ2=1.12, P=0.289 P>0.05 (NS)Nonaddicted 269 (43.2) 159 (41.6) 110 (45.9)
NS: Not significant
Table 5: Comparison of students with mild, moderate, and no Internet addiction on score on Big Five personality factors and Short‑Form Egna Minnenav Barndoms Uppfostran
Test I. Mild IA Median
II. Mode‑rate IA Median
III. No IA Median
KW test, P MW I versus II (U, P)
MW I versus III (U, P)
MW II versus III (U, P)
Big Five personality factorsConscientiousness 27 23 30 164.228, <0.001 1590.5, <0.001 8965.5, <0.001 1476, <0.001Agreeableness 28 24 32.5 244.905, <0.001 1551.5, <0.001 9957, <0.001 948, <0.001Extraversion 27 23 32 269.355, <0.001 1384, <0.001 5624.5, <0.001 489.5, <0.001Neuroticism 31 34 22 375.719, <0.001 4645.5, <0.001 2939.5, <0.001 195.5, <0.001Openness to experience 27 21 31 170.242, <0.001 1506, <0.001 9646.5, <0.001 1978, <0.001
Perceived parenting styleRejection 9 11 7 170.242, <0.001 3559, <0.001 7782.5, <0.001 1980.5, <0.001Emotional warmth 14 12 18 256.846, <0.001 2056.5, <0.001 5908.5, <0.001 2288.5, <0.001Overprotection 18 21 15 202.114, <0.001 4338, <0.001 8160, <0.001 1378.5, <0.001
KW: Kruskal‑Wallis, MW: Mann‑Whitney
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
148 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
Tabl
e 6:
Sum
mar
y of
biv
aria
te c
orre
latio
ns a
mon
g ke
y m
easu
res
Youn
g’s
Ext
rave
rsio
nA
gree
able
ness
Con
scie
ntio
usne
ssN
euro
ticis
mO
penn
ess
Rej
ectio
nW
arm
thO
verp
rote
ctio
nYo
ung’
sC
orre
latio
n co
effici
ent
1.00
0−0
.627
**−0
.604
**−0
.475
**0.
752*
*−0
.526
**0.
558*
*−0
.588
**0.
520*
*Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
0.00
00.
000
0.00
00.
000
0.00
00.
000
Extra
vers
ion
Cor
rela
tion
coeffi
cien
t−0
.627
**1.
000
0.51
8**
0.37
9**
−0.5
57**
0.42
0**
−0.4
22**
0.52
2**
−0.5
01**
Sign
ifica
nt (t
wo‑
taile
d)0.
000
.0.
000
0.00
00.
000
0.00
00.
000
0.00
00.
000
Agr
eeab
lene
ssC
orre
latio
n co
effici
ent
−0.6
04**
0.51
8**
1.00
00.
389*
*−0
.568
**0.
451*
*−0
.416
**0.
440*
*−0
.385
**Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
.0.
000
0.00
00.
000
0.00
00.
000
0.00
0C
onsc
ient
ious
ness
Cor
rela
tion
coeffi
cien
t−0
.475
**0.
379*
*0.
389*
*1.
000
−0.4
76**
0.31
2**
−0.3
74**
0.33
0**
−0.3
64**
Sign
ifica
nt (t
wo‑
taile
d)0.
000
0.00
00.
000
0.00
00.
000
0.00
00.
000
0.00
0N
euro
ticis
mC
orre
latio
n co
effici
ent
0.75
2**
−0.5
57**
−0.5
68**
−0.4
76**
1.00
0−0
.523
**0.
570*
*−0
.614
**0.
576*
*Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
0.00
00.
000
.0.
000
0.00
00.
000
0.00
0O
penn
ess
Cor
rela
tion
coeffi
cien
t−0
.526
**0.
420*
*0.
451*
*0.
312*
*−0
.523
**1.
000
−0.3
55**
0.45
3**
−0.4
42**
Sign
ifica
nt (t
wo‑
taile
d)0.
000
0.00
00.
000
0.00
00.
000
.0.
000
0.00
00.
000
Rej
ectio
nC
orre
latio
n co
effici
ent
0.55
8**
−0.4
22**
−0.4
16**
−0.3
74**
0.57
0**
−0.3
55**
1.00
0−0
.498
**0.
432*
*Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
0.00
00.
000
0.00
00.
000
.0.
000
0.00
0W
arm
thC
orre
latio
n co
effici
ent
−0.5
88**
0.52
2**
0.44
0**
0.33
0**
−0.6
14**
0.45
3**
−0.4
98**
1.00
0−0
.514
**Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
0.00
00.
000
0.00
00.
000
0.00
0.
0.00
0O
verp
rote
ctio
nC
orre
latio
n co
effici
ent
0.52
0**
−0.5
01**
−0.3
85**
−0.3
64**
0.57
6**
−0.4
42**
0.43
2**
−0.5
14**
1.00
0Si
gnifi
cant
(tw
o‑ta
iled)
0.00
00.
000
0.00
00.
000
0.00
00.
000
0.00
00.
000
IAT
= In
tern
et A
ddic
tion
Test
scor
e, *
*= P
<0.0
1
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
149Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
probably reflects the admission pattern of the medical institution.[27] However, both male and female groups were comparable in other aspects.
The majority of participants in the current survey were from urban areas and were well versed in new‑age technologies related to Internet use. Most of the students were staying in hostel accommodation with free Wi‑Fi. Therefore, most of the study participants had free and easy access to the Internet.
The parents of most of the students were educated, and hence, it can be assumed that most of the students had an environment encouraging the use of new‑age technologies which has been appropriately reflected in our study sample where the maximum number of students have started using the Internet in their adolescence by the age of 13 years.
Technological advancements have made the whole world available in the palm of our hands. With mobile phones
as efficient as a personal computer, it is slowly becoming the primary instrument to connect to the Internet. The smartphone is the new Swiss Army knife, from being available all the time and to be able to take calls, text, and many versatile usages, which makes them more than normal computers. Of the total participants in our study, 71.7% of the students were using their mobile to access the Internet which is far more than a laptop or desktop PC.
Especially in the context of India, cheaper mobile data over the past few years made a sizeable amount of people shifting to the mobile Internet connection. In 2014, the cost of one GB of mobile data was ₹270. Now, it is ₹10 per GB.[28] As a result, mobile data consumption has soared over the last few years. In our study, we found twice the number of mobile Internet users, as compared to the broadband Internet user. This can be explained by the free Wi‑Fi connection provided by the college.
Students spend most of the time at the college campus, but our finding indicated that most of them are online from hostel room, probably using the Internet in their spare time. Usage at day and night was almost similar, making the evening as the most connected time of day in our population. Two‑thirds of our sample were using the Internet on their mobile phone at home and college. A similar kind of result was observed by Chacko et al.[29]
A constant sum of money from monthly expenses was spent on Internet subscriptions, as the Internet is cheaper than ever before.[30] In the study, we observed that the majority were spending around 300 rupees a month on the Internet, with few students spending more than 600 rupees a month.
The speed of connection to the Internet is becoming constant and well above one Mbps in almost all locations
Table 7: Model summaryModel R R2 Adjusted R2 SE of the estimate1 0.800a 0.639 0.632 5.98960aPredictors: (Constant), overprotection, number, age, period, 1=Male, 2=Female, conscientiousness, openness, rejection, extraversion, agreeableness, warmth, neuroticism. SE: Standard error
Table 8: ANOVAa
Model 1
Sum of squares
df Mean square
F Significant
Regression 38789.418 12 3232.451 90.102 0.000b
Residual 21883.953 610 35.875Total 60673.371 622aDependent variable: Youngs By Internet Addiction Test score, bPredictors: (Constant), overprotection, number, age, period, gender, conscientiousness, openness, rejection, extraversion, agreeableness, warmth, neuroticism
Table 9: Coefficientsa
Model 1
Unstandardized coefficients Standardized coefficients β
t Significant 95.0% CI for BB SE Lower bound Upper bound
Constant 38.414 5.980 6.423 0.000 26.669 50.158Age −0.088 0.101 −0.022 −0.873 0.383 −0.286 0.110Gender 0.080 0.516 0.004 0.154 0.877 −0.933 1.092Period 0.369 0.288 0.032 1.282 0.200 −0.196 0.934Number 0.330 0.235 0.035 1.405 0.161 −0.131 0.792Extraversion −0.391 0.063 −0.195 −6.162 0.000 −0.516 −0.266Agreeableness −0.223 0.066 −0.109 −3.403 0.001 −0.352 −0.094Conscientiousness −0.200 0.066 −0.085 −3.037 0.002 −0.330 −0.071Neuroticism 0.609 0.066 0.361 9.276 0.000 0.480 0.738Openness −0.197 0.064 −0.091 −3.059 0.002 −0.323 −0.070Rejection 0.749 0.165 0.137 4.532 0.000 0.424 1.073Warmth −0.123 0.109 −0.038 −1.126 0.261 −0.338 0.092Overprotection 0.132 0.111 0.037 1.194 0.233 −0.085 0.350aDependent variable: Youngs By Internet Addiction Test score CI: Confidence interval, SE: Standard error
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
150 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
in India.[31] Almost all the students included in the study had a high‑speed Internet connection which indicates that slow speed is days of past.
The importance of the Internet has increased substantially in people’s life. Almost everyone at least checks for an update on social media and depends on news feeds for daily news. This ever‑increasing need of the Internet in our lives has created new challenges to societies worldwide. The problematic use of the Internet or IA per se measured by the criteria used was high in our study population. More than half of them (56.8%) fulfilled the criteria for IA. Many studies have reported a wide range of IA among a similar study population varying from 0.3% to 38% of participants.[32] In a Taiwanese study, 17.9% of students had IA,[33] whereas in Iran, the prevalence of IA in medical students was 10.8%.[34] In our study, none of the students reported severe IA, but previously, there have been studies that found severe addiction in their study population. An Iranian study found that 2.8% of their study population of medical students had severe IA.[34] The differences among these results may be due to variation in sample size, the methodology of the study, variation in the population, society and culture as well as time period of study.
The normal span of web utilization is the predominant variable influencing motivation behind Internet use. Studies have shown that short duration of Internet use by students is for homework, whereas engagement of longer duration indicates social media activities.[35] The maximum usage time of the Internet was between 2 and 4 h in this study, and most of the users were using the Internet for things apart from academics. All the participants were from medical colleges, and the involvement of technology has not penetrated this field compared to other science‑related streams. Medical education still relies hugely on books and clinical experience. Apart from researching the valuable resources not available in the college, the Internet does
not play a major role for medical students. Research is not so prevalent in undergraduate students, who were the major participant in our study, and most of them were using the Internet as a recreational tool.
One of the important purposes of Internet use in our population was online gaming. In the context of Internet “online gaming,” the trend of Western society is now seeping into our culture too. Online multiplayer games are overtaking conventional console games that existed before.[36] In the present study, 66% of the students were indulging in online gaming activity which consumed most of their time online. A similar finding was also observed in Iranian medical students, with 45.84% playing online games. This indulgence in online gaming may also affect the degree of Internet use by its users. This study showed that 8.5% of the population with IA had a predominance of online gaming as a major activity online. It was lower than that of a Hong Kong‑based study in which 15.6% of IAs were gamers.[37] This difference in values of game addicts and IA may be due to cultural differences as well as the study population.
In the present study, another important purpose for Internet use was music and video streaming which was much more consumed than games. Tons of video and audio streaming services exist today that make it easy to access and stream videos and music anywhere, anytime. Many users get most of their content streamed directly to their portable devices from the cloud. Almost three‑fourth of our study population used some form of streaming media service. These findings related to this purpose of Internet use are changing in different studies as streaming is becoming cheaper, faster, and easier day by day.[38]
Social networking has been found to be another important purpose of Internet use in our study. Millennials access various social networking sites in a day, such as Twitter, Snap Chat, Facebook, and Instagram.[39] Almost 90% of 18–29 years old regularly use social media sites.
Majority of people use multiple social media whenever they access the Internet.[40] As individuals are increasingly being occupied with modern stressful life, the use of social media acts as an easy way to be in touch with loved once without too much effort.[41] The reporting of similar finding around the world indicates that trends of the Internet are similar among students globally. There was no association of IA with gender in our study. However, usage pattern indicates that males use more online games, social media, and E‑mail whereas females stream more amount of video and music.
The pattern of Internet use is very similar to our social behavior. Personality influences behavior, and behavioral
0 20 40 60 80 100 120 140
78910111213141516
Frequency
Figure 1: Age at which Internet use started
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
151Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
level of curiosity.[15] The significant negative relation of openness with IA in this study may be attributed to the fact that though real and virtual life setting provides attractive opportunities to satisfy interest and curiosity to these individuals, virtual environment of the Internet does not provide realistic and live experience. Some studies indicate a positive relation between openness and IA[43,50] as well as no relation between them.[44,46,51] Further research is required with the specification of experience on both virtual and real levels.
A significant positive relation between neuroticism and IA was observed in this study. Those with this trait have high‑level experience of anxiety and worry. Due to these inherent traits, they may refrain from face‑to‑face communication and avoid social situations, having a self‑doubting attitude and underdeveloped self‑awareness. This may lead them to find solace on the Internet as it avoids face‑to‑face communication, and the individual can be anonymous on the web. Similar findings are observed in various other studies.[43,52,53]
The formation of one’s identity and personality is highly impacted by the relationship between a child and a parent.[54] Growing up with problematic and dysfunctional parenting, internalization and continuity of values become problematic increasing risks of psychopathology.[55] Indiscipline, violence, and low level of monitoring among families may make a way for problematic behaviors such as substance abuse, risk‑taking behavior, and IA. Parenting styles are one of the major determinants in nurturing behavior.[56]
When comparatively less amount of care, affection, comfort, support, or just love is received by a person from their parents and other caregivers, they feel rejected. Parental rejection is usually associated with various psychological and physically hurtful behaviors and negativity.[52] We found that parental rejection was a risk factor for overuse of the Internet as it was positively related to IA.
Rejection by parents makes individuals internalize a more hostile view of the world. This is because impaired self‑recognition[52] and low self‑identity may finally end up creating low self‑esteem.[57] Parental rejection may induce poor interpersonal problem solving which, in turn, leads them to be an object of discrimination. This could lead to a social deficit. To avoid social interaction, the individual turns to the Internet to fulfill the need for communication.
Exorbitant stress over children’s well‑being sometimes hinders the developmental needs. By not allowing a child to explore his or her interest, with equal opportunity of risk and responsibility, they may resist
patterns reflect personality. Personality is a combination of emotional characteristics, attitudes, and behavior of an individual. The rapid use of the Internet has, in turn, shed some light on examining how personality traits impact the use of technologies, particularly social networking, games, and so on. Assessment of personality traits based on the Big Five model of personality showed that agreeableness, conscientiousness, extraversion, and openness to experience had a negative relation with IA. Students having a low score on these traits were more likely to engage in frequent Internet use.
Individuals with the high amount of extraversion trait tend to spend their discretionary time in social engagements or activities which are not related to Internet use; they tend to engage in more human‑to‑human interaction than being alone or on computers.[42] This indirectly hinders them from IA. Extraverted individuals establish close and satisfying relationships in real life, lessening the tendency to do the same online.[43] IA in extraverted individuals may be at relatively lower rates explaining negative relation obtained in study and supported by many researches in literature.[44,45] Those with low extraversion trait have more free time and less social relationships in real life. As a result they are attracted to the Internet where they can focus their attention and remain alone.
Agreeableness in an individual makes them seek out group‑related activities, investing more time in interpersonal relationships, thus making less time available for Internet use as compared to those having a low score in agreeableness. Those with a low score on agreeableness traits are prone to show hostile and aggressive behavior and may prefer to show this behavior online as these kinds of behavior may have negative consequences in real life.[15] This factor may make some individuals with a low level of agreeableness prone to IA as confirmed in this study as well as supported by other studies in the literature.[46‑48]
Conscientiousness is a personality trait indicating the degree to which people are responsible and dependable. Students with high score in conscientiousness tend to be reliable, organized, rule‑following, and good self‑regulators. It has been argued that the wide‑open, unstructured environment of the Internet may not make it appealing to those with a high level of conscientiousness trait.[49] In student group, it may be that those with this trait are more engaged in participating in academic activities. They may still access the Internet for nonleisure purposes.
Individuals with openness to new experiences are imaginative, curious, and open‑minded having a high
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
152 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
a parent’s protection and find their opportunity to test their limit. The Internet provides a relatively easy and safe mean for this escape. Overprotection is a measure of this tendency and in this study showed a significant positive relation with IA.
Committed parents having a warm and equally assertive parenting style form a support system. They are responsible for the need of their children but protect the child from IA. This is supported by the fact that a strong negative association was observed between parents showing emotional warmth and IA.. Similar findings were reported in another study from China.[58]
LimitationAll the data acquired in this study are self‑reported, and no clinical interview was done on the student to diagnose IA. Being a cross‑sectional analysis, the cause‑and‑effect relation between associated factors could not be established. An observational longitudinal study could have given more information. However, the analysis of personalities is reasonable due to the stability of personalities over life. In this study, we asked for perceived parenting styles that are students describing their parents which may include biases further limiting our result as discrepancies may occur between individuals and parents on self‑reports of parenting styles.
ConclusionThe prevalence of some grade of IA in medical students was 56.81%, though no one had severe IA. There was no association of IA with gender. Usage pattern indicated that males use more online games, social media, and E‑mail, whereas females stream more of video and music. Personality traits of extraversion, openness to experience, agreeableness, and conscientiousness had a significantly negative relationship with IA, whereas neuroticism had a positive relation. This implies that students who were more engaged in social and academic activity, friendlier, more industrious, and who tended to seek new opportunities had less chance of being addicted to the Internet. On the other hand, students who were anxious and worried, introverted, and less rule‑bound tend to have a high chance of IA. Further, students with emotionally understanding parents, who gave an equal opportunity of freedom to them, made them less prone to IA.
Future directionsFurther research is needed to verify, clarify, and extend the present results, especially in different settings and populations, to generalize the above finding concerning other age groups and sociodemographic profile. Any
intervention and development of programs for the prevention and treatment of IA cannot be complete without considering personality traits and the role of parenting. Knowing personalities associated with excessive Internet usage may help in personalizing therapies for particular personalities. Major importance should be given for awareness of IA among students and faculties to detect an earlier sign of IA and reduce the risk of it becoming pathological. The role of parenting style may give clues to formulate and educate future parents and caregivers on how to connect with their children and make them less prone to IA.
Financial support and sponsorshipNil.
Conflicts of interestThere are no conflicts of interest.
References1. India Internet Usage and Telecommunications Reports;
2019. Available from: https://www.internetworldstats.com/asi a/in.htm. [Last accessed on 2019 Aug 03].
2. Young K. Internet addiction. Am Behav Sci 2004;48:402‑15.3. Chen K, Tarn M, Han B. Internet dependency: Its impact on
online behavioral patterns in E‐commerce. Hum Syst Manage 2004;23:49‑58.
4. Grant JE, Chamberlain SR. Impulsive action and impulsive choice across substance and behavioral addictions: Cause or consequence? Addict Behav 2014;39:1632‑9.
5. Yen JY, Ko CH, Yen CF, Chen SH, Chung WL, Chen CC. Psychiatric symptoms in adolescents with Internet addiction: Comparison with substance use. Psychiatry Clin Neurosci 2008;62:9‑16.
6. Lee HW, Choi JS, Shin YC, Lee JY, Jung HY, Kwon JS. Impulsivity in internet addiction: A comparison with pathological gambling. Cyberpsychol Behav Soc Netw 2012;15:373‑7.
7. Hamburger Y, Ben‑Artzi E. The relationship between extraversion and neuroticism and the different uses of the Internet. Comput Hum Behav 2000;16:441‑9.
8. Scealy M, Phillips JG, Stevenson R. Shyness and anxiety as predictors of patterns of Internet usage. Cyberpsychol Behav 2002;5:507‑15.
9. Leung L. Loneliness, self‑disclosure, and ICQ (“I seek you”) use. Cyberpsychol Behav 2002;5:241‑51.
10. Shaffer D. Social and Personality Development. 6th ed.. Belmont: Wadsworth/Thomson Learning; 2009. p. 37‑65.
11. Cervone D, Pervin LA. Personality: Theory and Research. 14th ed.. Oxford, England: John Wiley & Sons; 2018. p. 3‑25.
12. Fabiansson C. Pathways to Excessive Gambling: A Societal Perspective on Youth and Adult Gambling Pursuits. Abingdon: Rutledge; 2016.
13. Digman J. Personality structure: Emergence of the five‑factor model. Ann Rev Psychol 2003;41:417‑40.
14. Gaines S. Personality Psychology: The Basics. Abingdon: Routledge; 2019.
15. Graham EK, Lachman ME. Personality stability is associated with better cognitive performance in adulthood: Are the stable more able? J Gerontol B Psychol Sci Soc Sci 2012;67:545‑54.
16. John OP, Naumann L, Soto CJ. Paradigm shift to the integrative
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
153Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
Big Five taxonomy: History, measurement, and conceptual issues. In: John OP, Robins RW, Pervin LA, editors. Handbook of Personality: Theory and Research. 3rd ed.. New York, NY: Guilford; 2008. p. 114‑58.
17. Beal AC, Ausiello J, Perrin JM. Social influences on health‑risk behaviors among minority middle school students. J Adolesc Health 2001;28:474‑80.
18. Amato P, Fowler F. Parenting practices, child adjustment, and family diversity. J Marriage Fam 2002;64:703‑16.
19. Young K, Abreu C. Internet Addiction: A Handbook and Guide to Evaluation and Treatment. 3rd ed.. Hoboken, N.J.: John Wiley & Sons; 2011. p. 19‑35.
20. Samaha AA, Fawaz M, El Yahfoufi N, Gebbawi M, Abdallah H, Baydoun SA, et al. Assessing the psychometric properties of the internet addiction test (IAT) among lebanese college students. Front Public Health 2018;6:365.
21. Kayiş A, Satici S, Yilmaz M, Şimşek D, Ceyhan E, Bakioğlu F. Big five‑personality trait and internet addiction: A meta‑analytic review. Comput Hum Behav 2016;63:35‑40.
22. Benet‑Martinez V, John OP. Los Cinco Grandes across cultures and ethnic groups: Multitrait multimethod analyses of the Big Five in Spanish and English. J Personality Soc Psychol 1998;75:729‑50.
23. John OP, Donahue EM, Kentle RL. The Big Five Inventory – Versions 4a and 54. Berkeley, CA: University of California, Institute of Personality and Social Research; 1991.
24. Worrell FC, Cross WE. The reliability and validity of big five inventory scores with African American College students. J Multicultural Couns Dev 2004;32:18‑32.
25. Arrindell W, Sanavio E, Aguilar G, Sica C, Hatzichristou C, Eisemann M, et al. The development of a short form of the EMBU 1Swedish acronym for EgnaMinnenBeträffandeUppfostran (“My memories of upbringing”). 1: Its appraisal with students in Greece, Guatemala, Hungary and Italy. Pers Individ Dif 1999;27:613‑28.
26. Arrindell WA, Richter J, Eisemann M, Gärling T, Rydén O, Hansson SB, et al. The short‑EMBU in East‑Germany and Sweden: A cross‑national factorial validity extension. Scand J Psychol 2001;42:157‑60.
27. News I. More Women Study Medicine, but Few Practise | India News‑Times of India. The Times of India; 2019. Available from: https://timesofindia.indiatimes.co m/india/More‑women‑study‑medicine‑but‑few‑practise/articleshow/50525799.cms. [Last a ccessed on 2019 Oct 17].
28. Data Tariffs fall 93% in Last three Years: Telecom Department‑ET Telecom; 2019. Available from: https://telecom.economictimes.indi a t i m e s . c o m / n e w s / d a t a ‑ t a r i f f s ‑ f a l l ‑ 9 3 ‑ i n ‑ l a s t ‑ t h r e e ‑ years‑telecom‑department/63537339. [Last accessed on 2019 Oct 09].
29. Chacko H, Joseph J, Abraham J. ILL Effects of internet addiction‑knowledge and attitude among nursing students. Res J Comput and Inf Technol Sci 2015;3:1‑4.
30. McCarthy N. The Cost of Mobile Internet around the World; 2019. Available from: https://www.forbes.com/s i t e s / n i a l l m c c a r t h y / 2 0 1 9 / 0 3 / 0 5 / t h e ‑ c o s t ‑ o f ‑ m o b i l e ‑ internet‑around‑the‑world‑infographic/#71bd7556226e. [Last accessed on 2019 Oct 09].
31. Internet in India; 2019. Available from: https://en.wikipedia.org/wiki/Internet_in_India. [Last accessed on 2019 Oct 09].
32. Chakraborty K, Basu D, Vijaya Kumar KG. Internet addiction: Consensus, controversies, and the way ahead. East Asian Arch Psychiatry 2010;20:123‑32.
33. Tsai H, Cheng S, Yeh T, Shih C, Chen K, Yang Y, et al. The risk factors of Internet addiction – A survey of university freshmen. Psychiatry Res 2009;167:294‑9.
34. Ghamari F, Mohammadbeigi A, Mohammadsalehi N, Hashiani AA. Internet addiction and modeling its risk factors in medical students, Iran. Indian J Psychol Med 2011;33:158‑62.
35. Yu L, Shek DTL. Testing longitudinal relationships between internet addiction and well‑being in Hong Kong adolescents: Cross‑lagged analyses based on three waves of data. Child Indic Res 2018;11:1545‑62.
36. Smohai M, Urbán R, Griffiths MD, Király O, Mirnics Z, Vargha A, et al. Online and offline video game use in adolescents: Measurement invariance and problem severity. Am J Drug Alcohol Abuse 2017;43:111‑6.
37. Wang CW, Chan CL, Mak KK, Ho SY, Wong PW, Ho RT. Prevalence and correlates of video and internet gaming addiction among Hong Kong adolescents: A pilot study. ScientificWorldJournal 2014;2014:874648.
38. Hashemian A, Direkvand‑Moghadam A, Delpisheh A, Direkvand‑Moghadam A. Prevalence of Internet addiction in Iranian high school students a cross‑sectional study. JBRMS 2014;1:39‑44.
39. Zaremohzzabieh Z, Abu Samah B, Zobidah Omar S, Bolong J, Akhtar Kamarudin N. Addictive facebook use among university students. Asian Soc Sci 2014;10:33‑45.
40. Chou C, Condron L, Belland J. A review of the research on internet addiction. Educ Psychol Rev 2005;17:363‑88.
41. Whiting A, Williams D. Why people use social media: A uses and gratifications approach. Qual Market Res 2013;16:362‑9.
42. Loehlin J, McCrae R, Costa P, John O. Heritabilities of common and measure‑specific components of the big five personality factors. J Res Pers 1998;32:431‑53.
43. Rahmani S, Lavasani M. The relationship between internet dependency with sensation seeking and personality. Procedia Soc Behav Sci 2011;30:272‑7.
44. Buckner J, Castille C, Sheets T. The Five Factor Model of personality and employees’ excessive use of technology. Comput Hum Behav 2012;28:1947‑53.
45. Yan W, Li Y, Sui N. The relationship between recent stressful life events, personality traits, perceived family functioning and internet addiction among college students. Stress Health 2014;30:3‑11.
46. Andreassen CS, Griffiths MD, Gjertsen SR, Krossbakken E, Kvam S, Pallesen S. The relationships between behavioral addictions and the five‑factor model of personality. J Behav Addict 2013;2:90‑9.
47. Durak M, Senol‑Durak E. Which personality traits are associated with cognitions related to problematic Internet use? Asian J Soc Psychol 2014;17:206‑18.
48. Randler C, Horzum M, Vollmer C. Internet addiction and its relationship to chronotype and personality in a Turkish University Student Sample. Soc Sci Comput Rev 2013;32:484‑95.
49. King SA. Internet gambling and pornography: Illustrative examples of the psychological consequences of communication anarchy. Cyberpsychol Behav 1999;2:175‑93.
50. Hwang JY, Choi JS, Gwak AR, Jung D, Choi SW, Lee J, et al. Shared psychological characteristics that are linked to aggression between patients with Internet addiction and those with alcohol dependence. Ann Gen Psychiatry 2014;13:6.
51. Batıgün A, Kilic N. The relationships between internet addiction, social support, psychological symptoms and some socio‑demographical variables. Turk PsikolojiDergisi. 2011;26:1‑13.
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Shivam, et al.: Correlates of excessive Internet use
154 Medical Journal of Dr. D.Y. Patil Vidyapeeth ¦ Volume 14 ¦ Issue 2 ¦ March-April 2021
52. Cao F, Su L, Liu T, Gao X. The relationship between impulsivity and Internet addiction in a sample of Chinese adolescents. Eur Psychiatry 2007;22:466‑71.
53. Hardie E, Tee, M. Excessive internet use: The role of personality, loneliness and social support networks in internet addiction. Aust J Emerg Technol Soc 2007;5:34‑47.
54. Pedersen N, Reynolds C. Stability and change in adult personality: Genetic and environmental components. Eur J Pers 1998;12:365‑86.
55. Ryan RM, Lynch JH. Emotional autonomy versus detachment: Revisiting the vicissitudes of adolescence and young adulthood.
Child Dev 1989;60:340‑56.56. Kim EJ, Namkoong K, Ku T, Kim SJ. The relationship
between online game addiction and aggression, self‑control and narcissistic personality traits. Eur Psychiatry 2008;23:212‑8.
57. Kenny M, Rice K. Attachment to parents and adjustment in late adolescent college students: Current status, applications, and future considerations. Couns Psychol 1995;23:433‑56.
58. Yao MZ, He J, Ko DM, Pang K. The influence of personality, parental behaviors, and self‑esteem on Internet addiction: A study of Chinese college students. Cyberpsychol Behav Soc Netw 2014;17:104‑10.
[Downloaded free from http://www.mjdrdypv.org on Friday, September 3, 2021, IP: 183.83.132.78]
Copyright of Medical Journal of Dr. D.Y. Patil University is the property of Wolters KluwerIndia Pvt Ltd and its content may not be copied or emailed to multiple sites or posted to alistserv without the copyright holder's express written permission. However, users may print,download, or email articles for individual use.
Copyright of Medical Journal of Dr. D.Y. Patil Vidyapeeth is the property of Wolters KluwerIndia Pvt Ltd and its content may not be copied or emailed to multiple sites or posted to alistserv without the copyright holder's express written permission. However, users may print,download, or email articles for individual use.