Correlation between Smartphone Addiction, Sleep Quality and Physical Activity among Young Adults

A digital revolution was started in the 1990s by the introduction of Personal Computers (PC) and rapidly progressed to independent use of tablet PCs and smartphones [1]. The term smartphone was introduced in 1997 and has been ranked as a new class of mobile technology providing a number of facilities including voice and wireless communication and personal information management applications. The newer versions of the smartphones provide a greater access to the outside world through web browsing, Wi-Fi, third party applications etc; are more portable and hence attractive especially to the youth [2].

India stands in second position i.e., just behind China in wireless communication subscription worldwide. In September 2018, number of active wireless subscriptions in India was 1,013.23 million and is projected to increase largely in the next few years [3].

The smartphone revolution since 2000 is bringing noticeable changes in daily lives of people as it is providing more convenience in day to day life but along with that many adverse-effects in interpersonal relationships, psychological wellbeing and physical health. Considering the youth in the present scenario, they are the first generation to have grown up with so much exposure to high-tech media and this makes them more susceptible to the adverse-effects of smartphones and social media than older adults [1]. Excessive behaviour in using technology tools such as smartphones, android applications or its entertainments can be termed as mobile phone addiction or internet addiction [4]. Mobile phone use can be classified as being of a ’dangerous’ level when daily activities start being affected by it [5]. Smartphone usage can be considered as an antecedent of behavioural addiction and has been linked to side effects like lower academic performance, decreased real life social interaction and negative effects on relationships [5].

Previously, activities like internet browsing and updating social networking sites have been defined as sedentary behaviour. These sedentary or inactive behaviours can cause obesity and other metabolic disorders as it can lead to reduction in energy expenditure. These behaviours can also be associated with lower physical activity levels, in that they cause reduction or cessation of activities like outdoor games, walking and other forms of exercise [6]. Reduced cardiorespiratory fitness occurs as a result of sedentary behaviour. Spending more time using smartphones can also affect sleep. Proper sleep length and sleep quality is important for good emotional and physical well-being. Disruption of sleep including decreased sleep duration, sleep disturbances and daytime dysfunctions can even lead to low academic performance. Health can be directly influenced by sleep quality and duration. In 2000, Dement WC et al., reported that sleep is an active time in which many complex physiological, neurological and hormonal changes can occur. Chronic sleep deprivation also reduces the immune response of the body [7].

The relationship between smartphone use and physical activity, which includes walking, vigorous activities like aerobics and moderate activities like leisure time cycling, is obscure and controversial to some extent [8]. Many existing studies which were done on the association between use of electronic media and sleep were mainly focused on adolescents [9-11]. There were fewer studies which have investigated the relationship between smartphone addiction and sleep quality in young adults. As the youth have less parent-imposed constraints when compared to adolescents, they are more prone to overuse of smartphone or electronic media devices [5]. Studies relating to smartphone use and its relationship with components of well-being such as physical activity and sleep quality especially in the youth have not yet yielded conclusive results. Understanding this relationship further will help provide an insight into the extent to which smartphone use is affecting the youth. Thus, a need was identified to find if smartphone use, sleep quality and physical activity levels were related to each other. The present authors hypothesised that an increased level of smartphone use may be associated with decreased sleep quality and decreased physical activity levels. The aim of this study was to find out the correlation between smartphone addiction, sleep quality and physical activity in young college going adults.

Materials and Methods

This cross-sectional study was conducted in a health science college within city limits of Mangaluru, Dakshina Kannada, Karnataka, India in a period of two months, April and May 2019. A total of 113 students were enrolled for the study by convenience sampling. Ethical clearance for the study was obtained from the Institutional Ethical Committee (IEC no: AJEC/REV/64/2019). One week prior to the study, the students were verbally informed about the study to be conducted. A total of 120 students were screened for the study from which seven were excluded as two of them had a history of acute illness- fever, one had recently recovered from malaria, three were on medications for migraine and one was a non-smartphone user [Table/Fig-1]. Both men and women of age 19-25 who were using smartphones were included. A brief explanation about the procedure was given to all the participants following which a written informed consent was obtained from each of them. Each participant was given the questionnaires to fill up, with the examiner providing assistance as needed.

[Table/Fig-1]:

Flow chart of progress of participants through the study.

Outcome Measures

Reliable and valid questionnaires were used as outcome measures.

Smartphone Addiction Proneness Scale: This tool is a 4-point Likert’s scale (1=strongly disagree, 2=disagree, 3=agree, 4=strongly agree) that contains 15 items and is used to measure smartphone addiction. It contains four subdomains- disturbance of adaptive functions, virtual life orientation, withdrawal and tolerance. The level of smartphone addiction was categorised as high-risk (score ≥44), potential or dangerous risk (score 40-43) and no- risk (score ≤39) based on the scores. A higher score indicates higher degree of addiction [Annexure 1] [1,12].

PSQI: The PSQI is a self-reported questionnaire which measures sleep disturbances and quality over an interval of one month. It contains 19 self-rated questions which are divided into seven components like subjective sleep quality, sleep duration, sleep latency, habitual sleep efficiency, sleep disturbances, use of sleep medications and daytime dysfunctions each weighted on a 0-3 scale. Global PSQI score within the range 0-21 is obtained by adding all the seven component scores. Scores which are higher than 5 indicate worse sleep quality and less than or equal to 5 indicates good sleep quality [Annexure 2] [13].

IPAQ-SF: It is a 7 item self-rated scale which, based on the Metabolic Equivalent (MET) measures the frequency and duration of vigorous physical activities, moderate physical activities, walking and sedentary behaviour. A minimum of 1500 MET minutes a week are categorised as high, 600 MET minutes a week as moderate and if the subject is not meeting any of these criteria, then he/she is categorised as having low physical activity [Annexure 3] [8,14].

Statistical Analysis

The collected data were summarised using descriptive statistics, and the Karl Pearson’s correlation coefficient was calculated to find the correlation between the variables. All the data analysis was performed using SPSS 16.0 for Windows.

Results

A total of 113 young adults, 63 men and 50 women were included in the study. The descriptive statistics of age, SAPS, PSQI and IPAQ scores are given in [Table/Fig-2].

[Table/Fig-2]:

The mean age and mean scores of SAPS, PSQI and IPAQ.

Variables	Mean	Std. Deviation
Age	22.15	1.69
SAPS	36.27	10.95
PSQI	5.95	2.62
IPAQ	1288.15	1591.01

*PA: Physical activity

Majority of users (50%) had low physical activity, around (63%) had poor sleep quality while only 24.1% were at potential risk for smartphone addiction. The distribution of users in each category of IPAQ, SAPS and PSQI are shown in [Table/Fig-3].

[Table/Fig-3]:

Percentage distribution of participants under each category of IPAQ, SAPS and PSQI.

IPAQ	%	SAPS	%	PSQI	%
Low PA*	50.0	High risk	31.5	Good	37.0
Moderate PA	36	Potential risk	24.1	Poor	63.0
High PA	14	Normal users	44.4

[Table/Fig-4] It shows a moderately significant positive correlation between SAPS and PSQI scores and moderately significant negative correlation between SAPS and IPAQ scores.

[Table/Fig-4]:

Correlation between SAPS, PSQI and IPAQ.

	PSQI	IPAQ
SAPS pearson correlation	0.473**	-0.335**
Sig. (two-tailed)	0.001	0.001
N	113	113
PSQI pearson correlation		-0.189*
Sig. (two-tailed)		0.050

**Correlation is significant at the 0.01 level (two-tailed); *Correlation is significant at the 0.05 level (two-tailed)

Discussion

The present study was done with the objective of correlating smartphone addiction, sleep quality and physical activity among young adults. The rapid increase in the use of smartphones which has happened in recent years has made its users prone to smartphone addiction, which represents the merging of existing mobile phone and internet addiction problems into smartphone addiction. Various physical and psychological health problems like blurred vision, pain in the wrist or neck, anxiety, depression etc., are caused due to overuse of a smartphone [5]. The relationship between mobile phones, smartphones and the internet on one hand, and anxiety, depression, and sleep disturbances on the other in adolescents have been evaluated in some studies [15,16].

The present study showed a moderately positive significant correlation between smartphone addiction and sleep quality. An association between internet addiction and impaired sleep was found by Canan F et al., [9]. In terms of sleep duration, both internet use and the purpose of internet use are important. For example, using internet for social networking or watching online movies or videos at night are seen to lesser sleep durations [17]. Use of electronic media such as computers and smartphones at night are known to lead to depressive symptoms and disturbance of sleep. People with smartphones tend to sleep later with individual variations, but their sleep quality, i.e., the depth and restfulness of the sleep were not disturbed, according to a study done by Lemola S et al., [16]. Level of physical activity and risk of problematic internet use were seen to be inversely related to each other in a study conducted by Park S [18]. Excessive internet use or smartphone use especially during late hours of night can have indirect negative effects through sleep deprivation [13,19].

Sleep construction may be affected inversely by problematic internet use in that it may reduce slow-wave sleep, Rapid Eye Movement (REM) sleep, and sleep efficiency. The onset of sleep has been postulated to be delayed by the bright light of the computer screen by improving melatonin secretion [5,20]. There are some possible mechanisms concerning the relationship between electronic media use and poor sleep. Firstly, electronic media use may displace sleep; second, using electronic media devices may be associated with cognitive, emotional or physiological arousal; then, light emission of the screen of devices may affect sleep; and also mobile phone use in the bedroom may disturb sleep in that received messages may awake adolescents or youth at night [21].

Mobile phones emit electromagnetic fields which can have adverse-effects on sleep electroencephalograms. This electromagnetic field exposure also affects physiological factors such as sleep quality and the melatonin rhythm i.e., by affecting melatonin onset time. This probably happens by influencing the brain activity-particularly that of the pineal gland; it may also result in altered cerebral blood flow and brain electrical activity. Moreover, prolonged use of media can cause physical discomfort, such as muscle pain and headaches because of abnormal postures adapted during its use, which can negatively affect sleep [5,22].

In the present study, only a negligible negative correlation between sleep quality and physical activity and a negative moderate significant correlation between smartphone addiction and physical activity were found. This result is in line with the results of Park S, who found a direct association between physical activity and higher sleep satisfaction and inverse association between problematic internet use and physical activity among adolescents [18]. Smartphone addicts have less real life interaction with people outside and they may have reduced physical activity leading to obesity. This can consequently be harmful to physical health by resulting in higher fat mass and decreasing muscle mass induced by less physical activity [12]. This implicates the importance of physical activity and the detrimental effects of smartphone addiction on it. A study on prevalence of overweight and obesity among adolescent users of information and communication technology of age 14, 16 and 18 has found a significant association between the two [6]. Proper education and warning should be given to the smartphone users regarding the adverse health effects caused by over use of smartphones. To increase physical activity and health it is important to reduce sedentary behaviours including smartphone use, computer use and television viewing to less than two hours per day [23].

Limitation

These limitations of the present study should be considered. Firstly, self-rated subjective measures were used to assess physical activity and sleep quality. Secondly, the present authors could not establish a causal relationship between the variables because this is a cross-sectional study. Also, the correlation was not done separately in men and women participants. Lastly, all of the participants were health science college students, and may not represent the total population.

Conclusion

In high risk and dangerous users of smartphones, the quality of sleep and physical activity tends to decrease. Young adults showing insomnia symptoms should be attentively monitored for smartphone addiction.

*PA: Physical activity**Correlation is significant at the 0.01 level (two-tailed); *Correlation is significant at the 0.05 level (two-tailed)

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