Addiction-like behavior associated with social media usage in undergraduate students of a government medical college in Delhi, India.

BACKGROUND: Excessive use of social media is increasingly being recognized as a source of technological addiction in young people globally.
OBJECTIVE: The aim of this study is to assess social media addiction in medical students using a self-designed questionnaire.
MATERIALS AND METHODS: We collected data from undergraduate medical students (MBBS) in Delhi, India using a self-administered 20-item social media addiction questionnaire (SMAQ) to measure addiction-like behavior, and the Pittsburgh Sleep Quality Index (PSQI) to assess sleep quality.
RESULTS: We enrolled 264 (62.3%) male and 160 (37.7%) female participants of mean (standard deviation) age 19.83 (1.6) years. The Cronbach's alpha of the SMAQ was 0.879. A principal component analysis revealed a 4-component SMAQ structure based on eigenvalue cutoff (>1), loading score >0.3, and inspection of the Scree-plot that explained 54.7% of the total variance. We observed strong loadings of impaired control items on Component 1, decreased alternate pleasure items on Component 2, intense desire items on Component 3, and harmful use items on Component 4. The mean SMAQ score was significantly higher in the students reporting poor sleep quality and older students.
CONCLUSION: The SMAQ has acceptable psychometric properties, with higher scores associated with sleep deprivation. A majority of students were unable to reduce their time spent on social media despite wanting to do so, signifying the presence of tolerance and impaired control. Copyright:

INTRODUCTION

Social media constitutes a variety of internet applications that have provided >3 billion people with a platform to connect in real-time and share texts, messages, photos, and videos. The popularity of social media networks has exponentially increased in the previous decade due to the dissemination of affordable Internet and smartphone technology in developing countries, especially among their younger populations.[1] However, there is growing recognition that excessive use of social media is a form of behavioral addiction associated with high levels of anxiety and depressive symptomatology.[23] Some researchers have even compared extreme cases of addiction to social media comparable to substance-related addictions involving tobacco smoking or alcohol.[4]

Social media can promote the feeling of social envy and anxiety, and can potentially interfere with sleep.[5] Responding to late-night social media ping notifications on smartphones can reduce sleep quality, whereas blue light emissions can increase sleep latency by disturbing the circadian rhythm.[6] Furthermore, an extended number of hours spent on social media contributes to sleep displacement.[7] In younger age-group students, poor sleep quality can cause cognitive impairment and reduced concentration.[8] Studies have also linked excessive social media use with diminished academic performance in young students.[9]

The prevalence of social media addiction has been estimated to be particularly high among adolescents and young people in developed countries.[1011] India, the country with the largest youth population globally, has become a world leader in the adoption of smartphones and mobile data in the past 5 years, which has materialized the growth and popularity of social media use.[12] However, there are very few studies that have evaluated social media addiction in India, especially with locally validated questionnaires. A recent study estimated that 36.9% of students in Southern India had social media addiction by using a questionnaire adapted from Young's internet addiction test.[13] A previous study among medical students in Delhi had reported a high prevalence of mobile phone addiction, which coupled with academic stress and anxiety, possibly renders them susceptible to social media addiction and sleep deprivation.[14]

We conducted the present study to assess social media addiction in medical students using a self-designed questionnaire.

MATERIALS AND METHODS

Design, setting, and participants

We conducted a cross-sectional study among adult medical undergraduate (MBBS) and interns of a government medical college in Delhi situated in Northern India during September–November 2019. All the students could read, comprehend, and respond in the English language, and it is the official medium of instruction.

Study instruments

We constructed a 20-item social media addiction questionnaire (SMAQ) in the English language after the application of the following steps: (a). Identification of domains that corresponded to the International Classification of Diseases, 10th Revision criteria for substance dependence syndrome,[15] and the inclusion of items from the literature search and previously validated questionnaires related to behavioral and technological addiction.[141617] The SMAQ assessed the presence of intense desire (Q.1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 19), impaired control (Q. 3, 11, 12, 15, 16, 19), withdrawal (Q. 13), tolerance (Q. 5, 6, 11, 12, 16, 18), decreased alternate pleasure (Q. 5, 6, 7, 8, 9, 10, 13), and harmful use (Q. 14, 15, 17, 18, 19, 20). The SMAQ also corresponded to the four components of the CAGE screening questionnaire for potential drinking-related problems[18] and Griffith's six core components of addictions,[19] (b) Pretesting of the questionnaire was conducted in 10 students who were not part of the final study, (c) Content validity of the items was determined by two experts on behavioral health who went through each of the items and their pretest responses. Subsequently, they, by consensus, accepted the appropriateness of all the items subject to language modification in certain items. The response to the each of the SMAQ items was self-rated by the students on a 6-point Likert scale with options being 1 (strongly disagree), 2 (disagree), 3 (weakly disagree), 4 (weakly agree), 5 (agree), and 6 (strongly agree). The total SMAQ score was the sum of individual scores for all the 20 items of the questionnaire, with higher scores indicating a greater risk of addiction

Pittsburgh Sleep Quality Index (PSQI) - The PSQI is a valid instrument used to differentiate “poor” from “good” sleep by measuring seven domains: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, and sleep disturbances, use of sleep medication, and daytime dysfunction over the last month.[20] The cutoff for poor and good sleepers was considered at a PSQI score >6, which has been previously validated in Indian university students.[21]

Sampling and data collection

The college has five batches of undergraduate medical students for the MBBS course lasting for five and a half years duration. We selected a total of 95 students from among the 250 cohorts in each batch, with final year students and interns considered as one-batch during participant selection. A sample size of ≥400 with item-to-respondent ratio of 20:1 is considered excellent for factor analysis.[22] We selected the participants by simple random sampling using a computer-generated set of random numbers for selection through student roll numbers. The selected participants were administered the questionnaires in groups in a separate lecture room. An investigator was present at these sites during this time to resolve any participant query regarding filling of the questionnaires and also prevent any interpersonal interaction among the participants.

Statistical analysis

We analyzed the data with the IBM SPSS Statistics for Windows, Version 25.0 (Armonk, NY: IBM Corp.).

Handling of missing data

We assumed that the missing data was at random. We excluded questionnaires with more than ≥4 incomplete entries in the social media questionnaire. Missing items were imputed, taking the item median score as per the gender and age-group to which the participant belonged.

The quantitative data were expressed in terms of mean, median, and standard deviations (SDs) and qualitative data in terms of frequency and proportions. The significance of the association between categorical variables was determined by Chi-square/Fisher's exact test. The independent samples t-test was applied to test for the significance of the mean difference between groups. A P < 0.05 was considered statistically significant. We also conducted a principal component analysis (PCA) of the SMAQ.

Ethical considerations

The study was approved with an exemption from full review by the Institutional Ethics Committee of the medical college. We obtained written and informed consent from all the study participants, and we maintained data confidentiality, with the data being used for research purposes only.

RESULTS

Participant characteristics

We distributed a total of 475 questionnaires to medical undergraduate students and interns of the selected medical college with a response rate of 100%. We excluded 51 questionnaires with incomplete responses, and hence, the effective sample size was 424. We enrolled 264 (62.3%) male and 160 (37.7%) female participants. The mean (SD) age of the participants was 19.83 (1.6) years.

Social media usage

The total typical weekly mean (SD) time spent on social media by the participants was 21.8 (11.2) hours, with adolescents reporting significantly lower time spent on social media compared to older participants (P < 0.001), although no association existed with participant gender (P = 0.165). Popular social media platforms such as Facebook and YouTube were accessed more frequently by older or male students compared to adolescent or female students [Figure 1].

Figure 1

Social media usage in medical students of Delhi (n = 424). *Mean number of days accessed in a typical week

Psychometric properties of the social media addiction questionnaire

The Cronbach's alpha of the 20-item SMAQ was 0.879 and the split-half reliability coefficient was 0.765, indicating very good reliability. The dataset was assessed to be suitable for the application of PCA in terms of sampling adequacy. The overall Kaiser-Meyer-Olkin (KMO) measure was 0.89 classifications of “Meritorious” according to Kaiser. All the individual KMO measures were >0.8. The correlation matrix showed that all variables had at least one correlation coefficient >0.3. The Bartlett's test of Sphericity was statistically significant (P < 0.0001).

We found four components that had eigenvalues >1, which explained 30.4%, 10.5%, 7.4%, and 6% of the total variance, respectively, thereby cumulatively explaining 54.7% of the total variance. Visual inspection of the Scree plot also indicated that four components should be retained [Figure 2]. We observed strong loadings of impaired control items on Component 1, decreased alternate pleasure items on Component 2, intense desire items on Component 3, and harmful use items on Component 4. Component loadings and communalities of the rotated solution are presented in Table 1.

Figure 2

Scree plot of a 4-component social media addiction questionnaire

Table 1

Rotated structure matrix for principal component analysis with varimax rotation of a 4-component social media addiction questionnaire showing major loadings

Item	Component				Communalities
	1	2	3	4
SAS16	0.832				0.722
SAS15	0.735				0.629
SAS17	0.694			0.362	0.627
SAS12	0.683		0.326		0.591
SAS11	0.670				0.477
SAS10		0.695		0.319	0.588
SAS7		0.684	0.304		0.585
SAS9		0.630		0.388	0.548
SAS8		0.615			0.588
SAS13		0.478	0.312		0.473
SAS14		0.472		0.413	0.436
SAS6	0.390	0.465	0.412		0.563
SAS3			0.750		0.639
SAS1			0.655		0.496
SAS4			0.641		0.549
SAS2			0.608		0.445
SAS5		0.490	0.569		0.572
SAS19			0.320	0.687	0.592
SAS20				0.664	0.532
SAS18				0.598	0.476

Extraction Method: Principal Component Analysis Rotation method: Varimax with Kaiser normalization

Construct validity of the social media addiction questionnaire

On dichotomizing responses into “agree” and “disagree” categories, higher mean scores were seen for items 1, 2, 3, 6 (eye-opener/intense desire), 11 (cut-down/tolerance) and 11, 15, 16 (impaired control) [Table 2]. Older students compared to their junior counterparts were significantly more likely to agree that “life would be less interesting,” “they could not imagine living” and “felt unhappy and annoyed when not connected” to social media. The students with poor quality sleep were also significantly more likely to agree regarding the harmful consequences of social media use compared to good sleepers [Table 3]. The average time spent on social media showed a moderate correlation with the SMAQ score (r = 0.4, P < 0.001).

Table 2

Distribution of responses to the social media addiction questionnaire in medical students (n=424)

Item	Question	Corrected item-total correlation	Cronbach’s alpha if items deleted	Mean (SD)
1	Check my social media notifications as soon as I receive them	0.493	0.873	3.7 (1.6)
2	Check my social media notifications right after waking up from sleep	0.438	0.875	3.8 (1.8)
3	Check my phone for social media notifications even during classes	0.456	0.874	3.2 (1.7)
4	Constantly check my phone so as not to miss out on social media updates from groups/those I follow/followers	0.554	0.871	2.8 (1.6)
5	Cannot imagine living without social media	0.510	0.872	2.7 (1.6)
6	Prefer spending time on social media when alone	0.526	0.872	3.8 (1.6
7	Feel life will be very less interesting without social media	0.457	0.874	3.1 (1.5)
8	Prefer communication with friends and family through social media	0.306	0.879	3.0 (1.6)
9	Feel my online friends on social media are more interesting and captivating than those offline	0.406	0.876	1.9 (1.2)
10	Feel my online personality in the world of social media to be more popular compared to that offline	0.432	0.875	2.2 (1.4)
11	Often think that I should shorten my time spent on social media	0.414	0.876	4.2 (1.5)
12	Feel that I am increasingly spending more and more time on social media	0.563	0.871	3.6 (1.6)
13	Feel unhappy and annoyed when not connected to social media	0.589	0.870	2.6 (1.4)
14	Feel anxious and stressed on getting less than expected likes for a social media post like a picture or video	0.495	0.873	2.1 (1.4)
15	Feel that my academic performance and productively suffers due to excessive social media usage	0.548	0.871	3.3 (1.7)
16	Feel that I am wasting my time on social media	0.519	0.872	3.9 (1.6)
17	Feel tired and lack adequate sleep from excessive social media use	0.535	0.871	3.0 (1.7)
18	See social media as an escape from the real world	0.483	0.873	3.0 (1.7)
19	Compulsively check for social media notifications even in places where it is dangerous to do so like driving or crossing the street	0.488	0.873	2.0 (1.4)
20	Reading other people’s posts on social media makes me envious and feel that I am missing out on things	0.466	0.874	2.6 (1.6)

Table 3

Item agreement on the social media addiction questionnaire and association with age, gender, and sleep quality among medical students (n=424)

Item number	Agree	Gender		Age (years)		Sleep quality
		Male (n=264)	Female (n=160)	18-19 (n=187)	≥20 (n=237)	Good (n=276)	Poor (n=148)
1	249 (58.7)	157 (59.5)	91 (56.9)	106 (56.7)	143 (60.4)	157 (56.9)	92 (62.1)
2	262 (61.8)	166 (62.9)	95 (59.4)	108 (57.8)	154 (65)	170 (61.6)	92 (62.1)
3	197 (46.5)	120 (45.5)	77 (48.1)	83 (44.4)	114 (48.1)	125 (45.3)	72 (48.5)
4	152 (35.8)	100 (37.9)	52 (32.5)	60 (32.1)	92 (38.8)	101 (36.6)	51 (34.5)
5	133 (31.4)	85 (32.2)	48 (30)	49 (26.2)	84* (35.5)	76 (27.5)	57 (38.5)
6	254 (60)	155 (58.7)	98 (61.2)	112 (59.9)	142 (59.9)	159 (57.6)	85 (57.4)
7	184 (43.4)	118 (44.7)	66 (41.2)	68 (36.4)	116* (48.9)	104 (37.7)	80* (54)
8	162 (38.2)	106 (40.1)	56 (35)	71 (38)	91 (38.4)	102 (37)	60 (40.5)
9	48 (11.3)	31 (11.7)	17 (10.6)	18 (9.6)	30 (12.6)	26 (9.4)	22 (14.9)
10	83 (19.6)	54 (20.4)	29 (18.1)	36 (19.2)	47 (19.8)	45 (16.3)	38* (25.7)
11	304 (71.7)	181 (68.6)	122 (76.2)	127 (68)	177 (74.7)	190 (68.8)	114 (77)
12	230 (54.2)	144 (54.5)	85 (53.1)	96 (51.3)	134 (56.5)	143 (51.8)	87 (58.8)
13	110 (25.9)	73 (27.6)	37 (23.1)	37 (19.8)	73* (30.8)	68 (24.6)	42 (28.4)
14	88 (20.7)	57 (21.6)	31 (19.4)	33 (17.6)	55 (23.2)	54 (19.5)	34 (23)
15	197 (46.5)	120 (45.4)	77 (48.1)	84 (45)	113 (47.7)	113 (40.9)	84* (56.7)
16	260 (61.3)	162 (61.4)	98 (23.1)	115 (61.5)	145 (61.2)	152 (55)	108* (73)
17	172 (40.5)	102 (38.6)	70 (16.5)	78 (41.7)	94 (39.7)	98 (35.5)	74* (50)
18	164 (38.7)	102 (38.6)	62 (38.7)	72 (38.5)	92 (38.8)	91 (32.3)	73* (49.3)
19	73 (17.2)	49 (18.6)	24 (15)	28 (15)	45 (19)	40 (14.5)	33* (22.3)
20	133 (31.3)	81 (30.7)	52 (32.5)	53 (28.3)	80 (33.7)	78 (28.3)	55 (37.2)

*Statistically significant

Association with sleep quality

The mean (SD) global PSQI score was 5.66 (2.6). We classified 276 (65.1%) participants as having a good sleep (PSQI ≤6) and 148 (34.9) as having a poor sleep (PSQI ≥7). The mean SMAQ score was significantly higher in the students reporting poor sleep compared to those showing good sleep quality [Table 4].

Table 4

Construct validity of the social media addiction questionnaire in medical students (n=424)

Variable	Total (n=424)	SMAQ score Mean (SD) 60.9 (17.5)	Difference between means, 95% CI	P
Age (years)
18-19	187 (44.1)	58.8 (16.1)	3.7 (0.35-7.05)	0.028
≥20	237 (55.9)	62.5 (18.4)
Gender
Male	264 (62.3)	60.9 (17.5)	0.07 (−3.4-3.5)	0.968
Female	160 (37.7)	60.9 (17.6)
Sleep quality
Good	276 (65.1)	59 (17.7)	5.3 (1.8-8.8)	0.003
Poor	148 (34.9)	64.3 (16.7)

CI – Confidence interval; SMAQ – Social media addiction questionnaire; SD – Standard deviation

DISCUSSION

The exponential increase in social media users globally intensifies the need for its measurement, which is particularly challenging in the absence of validated instruments.[23] We found the 20-item SMAQ displayed acceptable psychometric properties for the assessment of self-reported social media addiction in young medical undergraduates. Social media addiction scores were significantly higher in poor sleepers compared to good sleepers. Furthermore, increased time spent on social media also correlated with higher addiction scores. The evaluation of item-responses of the SMAQ revealed that a majority of participants were unable to reduce their time spent on social media despite wanting to do so signifying the presence of tolerance and impaired control.

Although it is well-established that school-going adolescents are at high risk of social media addiction,[10] in the present study, college-going adolescents reported less likelihood of addiction-like behavior compared to their senior counterparts reiterating the persistent addiction potential of the technology among youth.

In this study, gender was not associated with the potential for social media addiction in contradiction to a previous study conducted in India that found male gender to be a risk factor.[13] However, another large-scale study in Norway found women to be predisposed to a higher risk of addiction to activities on social media[11] indicating nonavailability of any definite evidence in studies limited by the cross-sectional design.

The study revealed that one in three medical undergraduates experienced poor sleep, with bad sleepers more likely to report excessive social media use compared to good sleepers. This corroborates the evidence from previous studies, which also found worsening sleep with increasing duration of social media use.[7] Poor sleep has been previously linked to diminished academic performance.[724] In this study, nearly half (46.5%) of the students were in agreement with the view that excessive social media use was negatively affecting their academic performance. However, another study in Eastern India reported a majority of medical students having a positive perception of social media impact on their academic performance.[25]

Finally, most participants did not agree that social media diminished their interpersonal relationships, promoted narcissism, or impacted their self-esteem, in contradiction to a study in Norway,[11] suggesting significant cross-cultural differences in the long-term influence of social media on an individual's personality.

In conclusion, self-reported social media overuse leading to addiction-like symptoms was reported by a large proportion of medical undergraduates when assessed with a self-designed SMAQ. Despite the lack of compelling evidence for recognizing social media addiction as a disorder,[23] we found it was significantly associated with objective parameters like poor sleep quality.

There are certain limitations to the study. In the absence of an objective or gold standard for the measurement of social media addiction,[26] we could not determine a cutoff point for distinguishing addiction and lack of addiction. Moreover, as the collected data were self-reported, it is likely to be influenced by the social desirability bias. The test–retest reliability analysis was also not performed. The cross-sectional study design precluded the identification of any potential causality between addiction and adverse health, academic or interpersonal problems in the students. The estimated time spent on social media could be overestimated since multiple social media accounts can be handled simultaneously and often in short bursts rather than in prolonged sessions. Finally, we conducted the study in medical students who are more likely to have a better awareness of addiction compared to other student populations, reducing the generalizability of the study findings.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.