Abstract
Background:
The likelihood of the relation between Internet overuse and comorbid psychiatric conditions is on the rise. However, sleep disturbances are common psychiatric symptoms associated with internet overuse. Our objective was to examine the association of Internet overuse with excessive daytime sleepiness, sleep problems in professionals from India.
Materials and Methods:
This was a web-based cross-sectional study through a predesigned questionnaire which included various professional groups. The information included in the questionnaire was sociodemographic details, Young's internet addiction test (IAT) and Epworth sleepiness scale (ESS).
Results:
About 1.0% of total sample population had severe internet addiction whereas 13% were in the range of moderate internet addiction and the mean score on IAT was found to be 32 (standard deviation [SD] = 16.42). The mean duration of total night time sleep (5.61 ± 1.17) is significantly lower in participants with moderate and severe internet addiction (6.98 ± 1.12) compared to those with no and mild internet addiction. The mean scores of ESS were significantly higher in individuals with moderate and severe addiction (M = 10.64, SD = 4.79). We found that sleepiness while in 5 of the situations such as driving a car (χ2 = 27.67; P < 0.001), sitting and reading (χ2 = 13.6; P = 0.004), traveling in a car (χ2 = 15.09; P = 0.002), afternoon rest time (χ2 = 15.75; P = 0.001), and postlunch quiet time (χ2 = 24.09; P < 0.001), predicted membership to moderate-to-severe internet addiction, even after controlling for the confounding effects of age and gender.
Conclusions:
This study shows an association between Internet overuse, excessive daytime sleepiness, and other sleep problems. Clinicians should be proactive and conscious in scrutinizing the patients for internet addiction and its consequences.
Keywords: Addiction, internet, sleep
INTRODUCTION
Internet is no longer just used for educational and research purposes unlike in the past. Over the years because of accessibility and affordability, the number of users has increased day-by-day. With 2 billion global users, in India, there were a predicted total of 354 million internet users in 2015.[1] Adolescents and young adults are especially at increased risk for internet addiction and its consequences compared to the elderly.[2]
Internet addiction has been defined as “excessive or poorly controlled preoccupations, urges or behaviors regarding computer use and internet access that lead to impairment or distress.”[3] Although there are controversies over use of the term “addition,”[4] and many prefer to use terms - “problematic internet use,”[5]“excessive internet use,”[6] etc., all of these terms convey similar implications. Overall, this condition is defined as the inability of individuals to control the internet use, resulting in marked distress and/or functional impairment in daily life.[7,8,9]
Since the time Goldberg[10] introduced the term “internet addiction,” there is growing interest in this field. Multitude of studies conducted till date studied the prevalence, risk factors and consequences of internet addiction.[11,12] However, the gray zone still persists as it has not been given place in the existing classificatory systems such as DSM-5. The only behavioral addiction considered in the DSM-5 is the internet gaming disorder under conditions requiring further study.[13]
With the increase in time spent in the internet use various studies showed relation between growing internet use and comorbid psychiatric issues such as loneliness, depression, harm avoidance, anxiety symptoms, impulsivity, and attention-deficit–hyperactivity disorder.[14,15,16] Furthermore, individuals with excessive internet usage have less time to sleep and feel tired more often than not. Excessive daytime sleepiness (EDS) is associated with impaired workplace performance, injuries, and risk of drowsy driving.[17] Studies addressing this issue of internet overuse and EDS have been rarely carried out in India. A few studies available till date tell us about the prevalence of internet overuse in professional groups[18,19] where workplace functioning is of utmost importance.
MATERIALS AND METHODS
This was a web-based survey conducted between January and February 2018 (2 months) through predesigned online questionnaire (www.surveymonkey.com). The questionnaire was circulated by using E-mails, WhatsApp, Facebook, other messenger applications by the investigators of four medical colleges to their contacts, who included various professional groups such as teachers, engineers, nurses, and students. The study commenced after taking approval from Ethics Committee. The target population included was between 18 and 65 years of age, of either gender. The respondents could fill the survey only once through their respective devices that way maintaining authenticity of the sample. The information included in the questionnaire was sociodemographic details, Young's internet addiction test (IAT)[20] and the Epworth sleepiness scale (ESS).[21] For the IAT, we used 5 point Likert scale (1 = rarely, 2 = occasionally, 3 = frequently, 4 = often, and 5 = always); total scores ranging from 20 to 100. Final responses were analyzed using the appropriate statistical method.
The purpose of the present study was to examine the association of Internet overuse with EDS in professionals from India.
RESULTS
Out of the 2015 responses received, 233 were excluded due to incomplete responses. Hence, the overall sample included was 1782 [Figure 1]. Out of this sample, the groups we included were doctors, students (nursing and MBBS), and other professionals.
Figure 1.
Flow diagram illustrating inclusion of samples in the study
Sociodemographic data
In the final sample of 1782 completers of the online survey, 58.4% (n = 1040) were male, 41.6% (n = 742) were female. The mean age group was found to be 27.7 years. About 27.4% were doctors (Post MBBS, PGs), 38.3% were students, and 34.3% included other professionals. The proportion of individuals who stayed at home (n = 876%–49.2%) and away from home (n = 906%–50.8%) was almost similar in the current sample. Most commonly used gadget was mobile phone (n = 1611, 90.4%) followed by desktop/laptop (n = 171, 9.6%).
Scores of internet addiction and it is relation to sleep
The mean score on Young's IAT is 32 (standard deviation = 16.42), indicating that the most of the population was within the average user range. About 1.0% of the total sample population had significant problems with internet usage, whereas 13% were in the range of frequent/occasional problems, 62.9% of the sample were average internet users. About 23% of the sample scored even <20 suggestive of having no problem with their internet use.
To test our primary objective, we divided the overall sample based on IAT scores into two categories - none and mild (includes those with IAT scores <20 and 20–49), moderate and severe (includes those with IAT scores 50–79 and 80–100).
Sleep disturbances and internet addiction severity
In this study, the total sleep duration of the participants ranged between 4 and 10 h, whereas the mean sleep duration was found to be 6.7 h. About 66.2% reported some form of sleep disturbances. Among this lack of freshness after sleep was seen in majority (24.6%) followed by difficulty initiating sleep (17.9%), difficulty maintaining sleep (12.7%), and early morning awakening (11%), respectively.
As shown in Table 1, we can understand that the mean duration of total nighttime sleep is significantly lower in participants with moderate and severe internet addiction compared to those with no and mild internet addiction. Furthermore, we found out that participants with nighttime sleep disturbances had significantly higher severity of internet addiction. When different types of sleep problems were compared between both severity groups, lack of freshness of sleep was significantly higher in the moderate and severe addicts group compared to no and mild addicts. All other types of sleep problems such as getting up earlier than intended, intermittent awakenings, difficulty falling asleep were found to be at a similar rate across different levels of severity of internet addiction.
Table 1.
Sleep disturbances and relation to internet addiction
| Variables | Yes/no | Mean±SD/n; n (%) | t-test/χ2 (P) | |
|---|---|---|---|---|
| No-mild severe | Moderate-severe | |||
| Duration of sleep at night (h) | - | 6.98±1.12 | 5.61±1.17 | 17.74 (<0.001) |
| Sleep disturbances | Yes | 974 (63.6) | 205 (82) | 32.58 (<0.001) |
| No | 558 (36.4) | 45 (18) | ||
| Most common sleep problem | ||||
| Falling asleep | Yes | 277 (18.1) | 42 (16.8) | 0.24 (0.624) |
| No | 1255 (81.9) | 208 (83.2) | ||
| Intermittent awakenings | Yes | 195 (12.7) | 31 (12.4) | 0.02 (0.885) |
| No | 1337 (87.2) | 219 (87.6) | ||
| Getting up earlier than intended | Yes | 163 (10.6) | 33 (13.2) | 1.44 (0.230) |
| No | 1369 (89.4) | 217 (86.8) | ||
| Lack of freshness after sleep | Yes | 339 (22.1) | 100 (40) | 35.39 (<0.001) |
| No | 1193 (77.9) | 150 (60) | ||
SD – Standard deviation
Findings from Epworth sleepiness scale
The mean scores of Epworth sleepiness scores were significantly higher in individuals with moderate and severe addiction. These findings suggest that the higher the internet addiction the more it cause interference in daytime alertness [Table 2].
Table 2.
Relation between Epworth Sleepiness Scores and internet addiction scores
| Variable | n; n (%)/mean±SD | χ2 (P) | |
|---|---|---|---|
| None and mild | Moderate and severe | ||
| ESS total | 6.97 (3.89) (n=1532) | 10.64 (4.79) (n=250) | 13.34 (<0.001) |
| While in a vehicle, while stopped for a few minutes in traffic | |||
| Would never doze | 1215 (79.3) | 126 (50.4) | 133.35 (<0.001) |
| Slight chance of dozing | 223 (14.6) | 61 (24.4) | |
| Moderate chance of dozing | 68 (4.4) | 36 (14.4) | |
| High chance of dozing | 26 (1.7) | 27 (10.8) | |
| While sitting and reading | |||
| Would never doze | 512 (33.4) | 41 (16.4) | 123.08 (<0.001) |
| Slight chance of dozing | 651 (42.5) | 77 (30.8) | |
| Moderate chance of dozing | 281 (18.3) | 73 (29.2) | |
| High chance of dozing | 88 (5.7) | 59 (23.6) | |
| While watching TV | |||
| Would never doze | 717 (46.8) | 102 (40.8) | 44.16 (<0.001) |
| Slight chance of dozing | 552 (36.0) | 69 (27.6) | |
| Moderate chance of dozing | 201 (13.1) | 46 (18.4) | |
| High chance of dozing | 62 (4.0) | 33 (13.2) | |
| While sitting inactive in a public place (e.g., a theater or a meeting) | |||
| Would never doze | 745 (48.6) | 84 (33.6) | 74.51 (<0.001) |
| Slight chance of dozing | 530 (34.6) | 76 (30.4) | |
| Moderate chance of dozing | 189 (12.3) | 47 (18.8) | |
| High chance of dozing | 68 (4.4) | 43 (17.2) | |
| While as a passenger in a car for an hour without a break | |||
| Would never doze | 470 (30.7) | 56 (22.4) | 26.13 (<0.001) |
| Slight chance of dozing | 532 (34.7) | 72 (28.8) | |
| Moderate chance of dozing | 331 (21.6) | 62 (24.8) | |
| High chance of dozing | 199 (13.0) | 60 (24.0) | |
| While lying down to rest in the afternoon when circumstances permit | |||
| Would never doze | 205 (13.4) | 24 (9.6) | 40.92 (<0.001) |
| Slight chance of dozing | 444 (29.0) | 55 (22.0) | |
| Moderate chance of dozing | 471 (30.7) | 54 (21.6) | |
| High chance of dozing | 412 (26.9) | 117 (46.8) | |
| While sitting and talking to someone | |||
| Would never doze | 1217 (79.4) | 129 (51.6) | 127.08 (<0.001) |
| Slight chance of dozing | 229 (14.9) | 63 (25.2) | |
| Moderate chance of dozing | 71 (4.6) | 39 (15.6) | |
| High chance of dozing | 15 (1) | 19 (7.6) | |
| While sitting quietly after a lunch without alcohol | |||
| Would never doze | 488 (31.9) | 49 (19.6) | 63.94 (<0.001) |
| Slight chance of dozing | 560 (36.6) | 70 (28.0) | |
| Moderate chance of dozing | 324 (21.1) | 63 (25.2) | |
| High chance of dozing | 160 (10.4) | 68 (27.2) | |
SD – Standard deviation; ESS – Epworth Sleepiness Scale
It was also found that the participants with moderate-severe internet addiction had significantly high chance of dozing in all the eight situations listed out on ESS [Table 2].
RESULTS OF LOGISTIC REGRESSION
A logistic regression analysis was conducted with levels of internet addiction (no or mild level of addiction as one group; moderate or severe level of addiction as other group) as dependent variables, ESS categories as independent variables with age and gender as covariates. We found that sleepiness while in 5 of the situations such as driving a car (χ2 = 27.67; P < 0.001), sitting and reading (χ2 = 13.6; P = 0.004), travelling in a car (χ2 = 15.09; = 0.002), afternoon rest time (χ2 = 15.75; P = 0.001), and postlunch quiet time (χ2 = 24.09; P < 0.001), predicted membership to moderate to severe internet addiction, even after controlling for the confounding effects of age and gender. This model produced an overall Cox and Snell pseudo R2 = 0.139 (χ2 = 266.01; P < 0.001).
DISCUSSION
The current study determined the prevalence of internet addiction and patterns of EDS among professionals in India. This study has also provided an estimate of the sleep problems among the respondents.
The relation between sleep and excessive internet usage forms a vicious cycle. Several hypotheses put forward predict that excessive exposure to the light emitting diodes screens particularly before bedtime, disrupts the biological clock and the circadian rhythm, thus leading to a phase delay and a slowing of melatonin secretion.[22] According to existing literature, the consequences of this phase shift leads to leads to sleep disturbances with later bedtimes, shorter sleep duration, diurnal hypersomnolence, and headaches.[23,24] However, the vice-versa is also true, individuals who are predisposed to sleep disturbances or have existing sleep disturbances are likely to use internet as a measure to distract.[25]
The excessive amount of time spent online may directly reduce the total sleep time leading to a diagnosis of insomnia. Time spent online, although not assessed separately, is the basis for 6 (out of 20) items (i.e., 01, 02, 05, 06, 17, and 19) of the IAT, the scale used in our study. Moreover, validity studies conducting factor analysis also have found “time” to be a major factor.[26] Studies done till date to evaluate the relation between social media/internet usage and sleep have shown that excessive use of screen leads to sleep-related consequences such as getting to bed later in the night, needing more time to fall asleep, increased number of awakenings in the night, and difficulty in waking up and feelings of sleepiness in day. In addition, sleep quality of individuals with higher scores on internet addiction scale was worse when compared to those with a lower score. However, these studies were mainly focused on adolescents and school going children. Moreover, the sleep-related variables were assessed using semi-structured questionnaires.[17,27,28,29,30]
In our study, we found that the presence of sleep disturbances and lack of freshness after sleep were significantly higher among those with higher levels of internet addiction (moderate-severe group). Furthermore, the duration of night sleep was significantly lower in respondents with higher levels of internet addiction. These findings are similar to the studies done in India till now.[31] However, as to our knowledge, this is the first study from India focusing on internet addiction, sleep disturbances, and EDS. A few studies done from India assessing internet addiction and psychiatric comorbidities showed relation of internet overuse and personality characteristics,[32] depression, anxiety, well-being, and functioning.[19,33,34] We could not find any study from India that assessed the relation between daytime sleepiness and internet addiction using validated scale.
Our study is not without limitations. Predominantly, online nature of the study might have picked up the sample which used internet more compared to other population. Although we tried to include population from all the age groups, the predominant age group of the final sample was between 25 and 30 years thus limiting the representativeness of the sample. As it was a cross-sectional study, no causal relationships could be ascertained from the same.
CONCLUSIONS AND FUTURE DIRECTIONS
Internet has revolutionized various fields such as education, marketing, and social communication and so the number of internet users is increasing exponentially every year. Developing countries like India are not an exception to this. India lacks in literature on Internet addiction compared to western literature thereby showing the lack of awareness and also the need for more research in this field. The present study identifies the association between Internet overuse, EDS, and other sleep problems. As the number of Internet addicts will continue to grow, clinicians should be proactive in examining Internet addiction in cases of EDS.
Future studies should focus upon studying daytime sleep as a mediator between internet addiction and work performance in professionals.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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