|Year : 2021 | Volume
| Issue : 2 | Page : 113-118
Smart phone usage pattern and associated insomnia among undergraduate students of a Medical College in Chengalpattu district, Tamil Nadu: A cross-sectional study
Geetha Mani, Karthikeyan Elavarasan, Prasan Norman, Thirunaaukarasu Dhandapani
Department of Community Medicine, Karpaga Vinayaga Institute of Medical Sciences and Research Centre, Chengalpattu, Tamil Nadu, India
|Date of Submission||14-Dec-2020|
|Date of Acceptance||22-May-2021|
|Date of Web Publication||24-Dec-2021|
Dr. Geetha Mani
Plot No. 428, Chozhan Street, Arul Nagar, Nandhivaram Guduvancheri, Chengalpattu - 603 211, Tamil Nadu
Source of Support: None, Conflict of Interest: None
Introduction: With increased integration of technology into medical education, smart phones have become an indispensable tool. Excess exposure to smart phones and its inadvertent use result in adverse health consequences, both physical and psychological. This study was planned to assess smart phone usage pattern and prevalence of smart phone addiction among undergraduate medical students and to identify association between smart phone usage and insomnia.
Material and Methods: A descriptive, cross-sectional study was conducted among undergraduate students of a medical college in Chengalpattu, Tamil Nadu, during January and February 2020. A total of 221 students from first, second, and third year MBBS participated. A Google Form with informed consent, smart phone usage practices, Smartphone Addiction Scale-Short Version (SAS-SV), and Athens Insomnia Scale (AIS) was used as study tool. Data were summarized as percentages, mean, and standard deviation and appropriate statistical tests of significance applied using SPSS software.
Results: Approximately half the students (49.3%) used smart phones for up to 3 h daily. Online videos (37.5%) and social media (34.9%) were the most common applications used; 39.4% skipped night-time sleep to use smart phone. The prevalence of smart phone addiction and insomnia was 23.5% and 30%, respectively. Gender, duration of use, time spent in online chats, and Internet search were significantly associated with insomnia; 51.9% of those with smart phone addiction reported insomnia (P < 0.05).
Conclusion: The prevalence of smart phone addiction and associated insomnia are high among medical students. With evolving need for technology in medical education, it is imperative that students are sensitized to rational use of smart phones.
Keywords: Insomnia, medical students, sleep disturbances, smart phone addiction, smart phone dependence, smart phone use
|How to cite this article:|
Mani G, Elavarasan K, Norman P, Dhandapani T. Smart phone usage pattern and associated insomnia among undergraduate students of a Medical College in Chengalpattu district, Tamil Nadu: A cross-sectional study. Indian J Community Fam Med 2021;7:113-8
|How to cite this URL:|
Mani G, Elavarasan K, Norman P, Dhandapani T. Smart phone usage pattern and associated insomnia among undergraduate students of a Medical College in Chengalpattu district, Tamil Nadu: A cross-sectional study. Indian J Community Fam Med [serial online] 2021 [cited 2022 Jan 23];7:113-8. Available from: https://www.ijcfm.org/text.asp?2021/7/2/113/333659
| Introduction|| |
The advent of smart phones and their various versions has revolutionized the way people interact and work in the last few decades. The number of smart phone users globally has increased from 2.5 billion in 2016 to an approximate 3.5 billion users in the year 2020. Worldwide, the age group of 18–34 years is found to have the highest smart phone usage rate of 62%. Fifty percent of android Smartphone users and 43% of apple iPhone users are younger than 34 years of age. An approximate 53% of smart phone users are males and 47% are females.
With increasing integration of technology in medical education, use of smart phones has become an essential tool for students. COVID19 pandemic and the ensuing lockdown with a complete shift to online learning have further incorporated smart phones into regular teaching-learning and assessment systems. The dependence of smart phones among young people and its inadvertent use makes it a double-edged weapon. The use for academic purposes also exposes them to various other applications which may disrupt their attention to academics. In addition, there are possible reported adverse health consequences.,, These health effects may be physical such as risk of premature diabetes mellitus, hypertension, cardiac diseases, ocular or auditory ailments, and musculoskeletal disorders or psychological such as altered sleep or diet patterns, addiction behavior, low self-esteem, and risk behavior.,, The distractions integral to smart phones have been reported to cause increased stress levels, poor sleep induction, insomnia apart from direct or indirect interruption to patient care.,, Inculcating rational smart phone utilization among medical students is the need of the hour to ensure healthy physicians and responsible patient care in future. This study was planned as a reflection exercise for students to assess the extent of their smart phone usage practices and its impact on sleep. The objectives of the study were to assess smart phone usage pattern and prevalence of smart phone addiction among undergraduate medical students in a medical college in Chengalpattu district, Tamil Nadu, and to identify association between smart phone usage and insomnia among the study population.
| Material and Methods|| |
A cross-sectional study was conducted among undergraduate medical students of a medical college in Chengalpattu district, Tamil Nadu during January and February 2020. Based on a study by Dharmadhikari et al. among medical students in Maharashtra, where the prevalence of smart phone addiction was 46.15%, the required sample size was calculated using the formula 4pq/d2, where P = 46.15%, q = 53.85% and d as an absolute error of 7%. The sample size derived was 203 and assuming a nonresponse rate of 10%, the final sample size was approximated to 225. The first, second and third year students were chosen to participate in the study and 75 students from each batch were selected by simple random sampling using the list of students in each batch as sampling frame. The selected students were invited to participate in the study.
The study was approved by the Institutional Ethics Committee. The participation was voluntary. A pretested, semi-structured questionnaire was prepared by Google survey forms and sent to selected students through Whatsapp or E-mail. The complete information about the study and its implications were described in the title page of the Google survey form and the questionnaire was applied after the participants have declared that they have read the information and consent to participate in the study. The participants were given the option to withdraw from study at any stage before submission of responses. Complete confidentiality of responses and privacy of students was ensured.
The questionnaire consisted of the following sections: basic identification details, availability of smart phones, time spent on smart phone for various purposes, impact of smart phones on daily activities, night time use of smart phones, Smartphone Addiction Scale-Short Version (SAS-SV) developed by Min-Kwon and Athens Insomnia Scale (AIS).,, The SAS-SV consists of 10 items rated on Likert scale from 1 to 6 (1 - strongly disagree to 6 - strongly agree). The sum of the individual scores was added to derive the final score. SAS-SV has been found to be internally consistent (Cronbach's α, 0.844) and stable over 1 week in various studies. The AIS consists of 8 items and evaluates sleep onset, night and early-morning waking, sleep time, sleep quality, frequency, and duration of complaints, distress caused by experience of insomnia and interference with daily functioning. Developed by Soldatos et al., it has been recorded to have an internal consistency ranging from 0.87 to 0.89 and a test–retest reliability of 0.88–0.89.
The responses were saved in Microsoft Excel spreadsheet format. Statistical analysis was performed using the IBM SPSS Statistics for Windows, version 23.0 (IBM Corp., Armonk, New York, USA). Categorical variables such as baseline characteristics, smart phone usage pattern, prevalence of smart phone addiction, and insomnia among participants were summarized as frequencies and percentages. Continuous variables such as SAS-SV and AIS scores were summarized as mean and standard deviation (SD). Chi-square test was performed to identify statistical significance of relationship between smart phone usage and insomnia among study participants. Student's t-test was used to compare mean AIS score among those with presence or absence of smart phone addiction. A P ≤ 0.05 was considered statistically significant.
Smartphone addiction was defined as a SAS-SV score more than 31 for boys and 33 for girls. A person was considered to have insomnia if the AIS score is 6 or above.
| Results|| |
Out of the 225 randomly selected students, a total of 221 students had provided complete responses. Both SAS-SV and AIS scales were found to have high internal consistency on reliability analysis in our sample population with Cronbach alpha values of 0.892 and 0.824 respectively. Among the 221 participants, 127 (57.5%) were females and 94 (42.5%) were males. The number of students from first, second, and third year were 81 (36.7%), 66 (29.9%) and 74 (33.5%) respectively; 187 students (84.6%) had single smart phone, 26 (11.8%) owned two and 8 students (3.7%) had three smart phones. [Table 1] showcases the distribution of duration of smart phone use for various activities among the participants and [Table 2] highlights their frequency of skipping routine academic or social activities due to smart phone use.
|Table 1: Distribution of duration spent in various activities using smart phone among participants (n=221)|
Click here to view
|Table 2: Distribution of frequency of skipping routine academic and social activities due to smart phone use (n=221)|
Click here to view
During daytime, 43 students (19.5%) reported having their smart phones always at a distance of 5–10 cm and 82 students (37.1%) reported having it within 10–20 cm. Only 12 students (5.4%) kept their smart phones switched off or in silent mode during sleep; 35 students (15.8%) reported having it within 5–10 cm and 46 students (20.8%) reported keeping them within 10–20 cm.
Based on responses to SAS-SV, 52 students were found to have smart phone addiction with a prevalence of 23.5% (17.9 to 29.1). The mean SAS-SV score among the participants was 26.14 ± 10.38.
With AIS score of more than 6, 67 students were categorized to have insomnia with a prevalence of 30.3% (24.3 to 36.4). The mean AIS score was 4.32 ± 3.67 [Table 3].
|Table 3: Distribution of perceived sleep disturbances among study participants (Athens Insomnia Scale) (n=221)|
Click here to view
Male gender, increased duration of time spent in smart phone use in general, increased time spent in online chats, internet search, and online video-streaming were significantly associated with presence of insomnia (P ≤ 0.05) [Table 4]. The mean AIS score among those participants with smart phone addiction was 6.25 ± 4.4 and those without smart phone addiction was 3.72 ± 3.2. The difference was statistically significant (P-value <0.001) [Table 5].
|Table 4: Distribution of insomnia among medical students based on baseline characteristics and smart phone usage practices (n=221)|
Click here to view
|Table 5: Distribution of insomnia among participants based on smart phone addiction (n=221)|
Click here to view
| Discussion|| |
A total of 221 first, second, and third year medical undergraduate students participated in our study.
Approximately half of our study population (49.3%) spent up to 3 h using smart phone for various activities, while an equal proportion of students used their smart phone for more than 3 h, out of whom 17.2% used smart phone for more than 5 h. In Sharma et al. study, 75% students spent 3–6 h using internet in smart phone for multiple purposes. Though the comparison is between two different characteristics, the fact that more than half the students spent a minimum of 3 h and above on smart phones, points to a substantially higher smart phone use in both studies.
Online video-streaming services (37.5%) and social networking sites (34.9%) were the most frequently used services. The predominant use of social media sites was also reported among medical students in similar studies by Dharmadhikari et al. in Maharashtra and Sharma et al. in Rajasthan., Increased smart phone use predisposes to procrastination or skipping of many routine activities. In the present study, night-time sleep (39.4%) was the most common routine activity skipped due to smart phone use, followed by sports and physical activity (28.9%) and academic activities (24.5%). Amra et al. in their study among adolescents in Iran reported a concordant finding of higher proportion of night-time use of smart phones.
In our study, 23.5% of the students had smart phone addiction as measured by SAS-SV, which was comparable to Brubaker and Beverly study among osteopathic medical students from Athens (22.3%). The prevalence was considerably lower compared to the findings of Dharmadhikari et al. from a medical college in Maharashtra where 46.15% of participants had smart phone addiction. In contrast, Alkhateeb et al. in their study among university students in Saudi Arabia reported a remarkably low prevalence of 14.7% among medical students. Sharma et al. study among medical students in Rajasthan report that 57.29% students suffer from Nomophobia or the fear of being without mobile phone contact. Shankar et al. in a sample population with predominantly adolescents and young adults in India, identified a prevalence of nomophobia to be 40.93%. The wide range in the prevalence of smart phone addiction or dependence as reported in above studies could be accounted for by the use of different scales of assessment. However, the high figures in comparable studies from diverse parts of the world point to the growing dependence on smart phones among young medical students.
The prevalence of insomnia was 30.3% as reported in current study. Although it points to a substantial problem, it is considerably lower compared to Bayatiani et al. study from Iran where 39.7% had insomnia, Jniene et al. study among medical students in Morocco, Amra et al. study from Iran and Brubaker and Beverly study from Athens where 35.3%, 42.5%, and 66.2% students had poor sleep quality, respectively.,,, Despite the differences, all studies including the current study, report a considerable burden of poor sleep quality or insomnia in association with smart phone usage, which highlights the need for priority action among young students.
In our study, males had a higher prevalence of insomnia compared to females as measured by AIS, and the difference was statistically significant. This was in contrast to Amra et al. study and Bayatiani et al. study where a higher proportion of females had insomnia or poor sleep quality., With increasing duration of use of smart phones, there was a proportionate increase in the prevalence of insomnia and this relationship was statistically significant on multinomial logistic regression analysis. This was in concordance with Amra et al. study where participants with poor quality of sleep had a mean duration of cell phone use of 5 h 58 min which was higher compared to those with good quality of sleep. Huang et al. in a preliminary study among Chinese college students also reported poor quality of sleep among students with excessive smart phone use for more than 5 h. Tamura et al. and Tokiya et al. reported similar association between duration of smart phone use and insomnia among Japanese adolescents.,
More than half the participants (51.9%) in our study with smart phone addiction reported insomnia and the distribution was statistically significant. In addition, there was a statistically significant difference between the mean AIS scores among those with smart phone addiction compared to those without smart phone addiction. Brubaker and Beverly study also revealed a significant positive relationship between smart phone addiction and poor sleep quality.
Our study has its limitations. This being a cross-sectional study, the causal relationship could not be proved. The study was conducted among students of a single medical institution and the findings could not be generalized to other states or countries with vast sociocultural and geographical differences. Although complete privacy and confidentiality was ensured, self-administered surveys may have an element of subjective bias. Despite the limitations, the study offers a timely insight into the smart phone usage pattern and associated sleep disturbances among medical students. This study conducted during the early stages of pandemic and before the implementation of lockdown and shift to online learning, has the potential to serve as a baseline study to compare any future studies on distribution of smart phone usage practices and associated adverse effects among medical students.
| Conclusion|| |
The prevalence of smart phone addiction and associated insomnia are high among medical students. With the evolving need for smart phone technology in medical education as a consequence of the pandemic and the shift to online learning methods, it is imperative that students are sensitized to rational and responsible use of smart phones as part of promoting positive health behavior.
The authors are thankful to the students for their enthusiastic participation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Alkhateeb A, Alboali R, Alharbi W, Saleh O. Smartphone addiction and its complications related to health and daily activities among university students in Saudi Arabia: A multi-center study. J Fam Med Prim Care 2020;9:3220-4.
Shoukat S. Cell phone addiction and psychological and physiological health in adolescents. EXCLI J 2019;18:47-50.
Tamura H, Nishida T, Tsuji A, Sakakibara H. Association between excessive use of mobile phone and insomnia and depression among Japanese adolescents. Int J Environ Res Public Health 2017;14:701.
Atherley A, Hu W, Teunissen PW, Hegazi I, Dolmans D. Appraising the use of smartphones and apps when conducting qualitative medical education research: AMEE Guide No. 130. Med Teach 2021;43:68-74.
Dharmadhikari SP, Harshe SD, Bhide PP. Prevalence and correlates of excessive smartphone use among medical students: A cross-sectional study. Indian J Psychol Med 2019;41:549-55.
] [Full text]
Kwon M, Kim DJ, Cho H, Yang S. The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS One 2013;8:e83558.
Soldatos CR, Dikeos DG, Paparrigopoulos TJ. Athens insomnia scale: Validation of an instrument based on ICD-10 criteria. J Psychosom Res 2000;48:555-60.
Luk TT, Wang MP, Shen C, Wan A, Chau PH, Oliffe J, et al.
Short version of the smartphone addiction scale in Chinese adults: Psychometric properties, sociodemographic, and health behavioral correlates. J Behav Addict 2018;7:1157-65.
Sharma N, Advani U, Sharma L, Jain M, Sharma K, Dixit AM. Pattern of mobile phone usage among medical students. Int J Acad Med 2019;5:118-23. [Full text]
Amra B, Shahsavari A, Shayan-Moghadam R, Mirheli O, Moradi-Khaniabadi B, Bazukar M, et al.
The association of sleep and late-night cell phone use among adolescents. J Pediatr (Rio J) 2017;93:560-7.
Brubaker JR, Beverly EA. Burnout, perceived stress, sleep quality, and smartphone use: A survey of osteopathic medical students. J Am Osteopath Assoc 2020;120:6-17.
Shankar V, Singh K, Jangir MK. Nomophobia: Detection and analysis of smartphone addiction in Indian perspective. Int J Appl Eng Res 2018;13:11593-9.
Jniene A, Errguig L, El Hangouche AJ, Rkain H, Aboudrar S, El Ftouh M, et al
. Perception of sleep disturbances due to bedtime use of blue light-emitting devices and its impact on habits and sleep quality among young medical students. Biomed Res Int 2019;7012350. doi: 10.1155/2019/7012350.
Bayatiani MR, Seif F, Bayati A. The correlation between cell phone use and sleep quality in medical students. Iran J Med Phys 2016;13:8-16.
Huang Q, Li Y, Huang S, Qi J, Shao T, Chen X, et al.
Smartphone use and sleep quality in Chinese college students: A preliminary study. Front Psychiatry 2020;11:352.
Tokiya M, Kaneita Y, Itani O, Jike M, Ohida T. Predictors of insomnia onset in adolescents in Japan. Sleep Med 2017;38:37-43.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]