INTRODUCTION
Smartphones are mobile phones that perform many of the functions of a computer, typically having a touch screen interface, internet access and an operating system capable of running downloaded applications. With market competition and pricing, smartphone once considered a luxury had become everyday gadgets for people across the globe. India stands to be the major market of exponential growth for suppliers of smartphones.[1]
A device developed to help long-distance communication had turned out to be next to everything in our lives such as internet access, social networking, personal diary, E-mail dispatcher, calculator, calendar, video game player, camera, and music player.[2] With a multiplicity of use it becomes difficult to recognize the distinction between normal and deviant behavior. These days, people were behaviorally conditioned to be alert for notifications from our phones. They often pull out their phones, driven by reflex as well as by anxiety to make sure they have not missed out on anything and anticipation of call or text.[3]
“Nomophobia” is the term used to define fear of being without a mobile phone, a combination of the words “no-mobile phobia.” It refers to discomfort, anxiety, nervousness, or anguish caused by being out of contact with mobile phone[3] and been considered as one among the eight mental illnesses caused by the internet. There were proponents for the inclusion of nomophobia in Diagnostic and Statistical Manual of Mental Disorders-5.[4] With the increasing availability and reduced pricing both smartphone usage and its dependence is bound to increase.
Although the disorder been frequently studied and reported among the young,[3,5–9] the behaviors seem to span across age with varying intensity. Hence, the study was designed with the objectives to estimate the prevalence of nomophobia in adults and determine its predictors and association with smartphone use patterns.
METHODOLOGY
After obtaining approval from the Institutional Ethics Committee, an online survey was conducted over a period of 6 months (September 2017–February 2018). Participants above 18 years, with access to the Internet and can read English were included in our study.
A web link was created with the first page describing principal investigator’s information and the objectives of the study. Informed consent to participate and publication of results were obtained at the start of the survey. The web link was posted on the social networks (Facebook and WhatsApp) of the principal investigator for participants to access and answer the survey. Participants were requested to share the link with their acquaintance and data collected using the snowball sampling.
Participation was completely voluntary, no incentives were provided for participation. Participants were ensured anonymity (no names required) and confidentiality of data collected. The survey required 10–15 min to complete.
Survey questionnaire
A semi-structured questionnaire was designed for the study having four sections. Section 1 was used to collect sociodemographic data including age, gender, domicile, education, occupation, income, and marital status. Section 2 consisted of smartphone usage details of participants such as owning a smartphone, type of network, data consumed per month, hours of use for recreational purpose, monthly expenses on recharge, age when started using mobile phone and smartphone. Other items included were reasons to smartphone use (for checking social media, E-mails, gaming, listen to music, texting, talking, look for information in Internet, news updates, and as planners), and usual situations or context of smartphone use (when bored, when alone, waiting for someone or something, while in classrooms or meetings, on public transport, after waking up, and use sacrificing sleep).
Section 3 and 4 included Nomophobia Questionnaire (NMP-Q),[10] A 20 item questionnaire, with responses measured in a 7 point Likert scale responses ranging from 1 (strongly disagree) to 7 (strongly agree). They were designed to assess 4 dimensions of nomophobia which were (1) Not being able to communicate, (2) Losing connectedness, (3) Not being able to access information and (4) Giving up convenience. Scores range from 20 to 140, with higher scores corresponding to greater nomophobia severity. The overall reliability is 0.945.
Statistical analysis
Statistical analysis was performed by licensed SPSS 20.0 version software (IBM SPSS Statistics for Windows, version 20.0, Armonk, New York, USA). For continuous data, the mean and median were calculated. For categorical data such as sociodemographic, smartphone use related data, reasons and context for smartphone use frequency distribution was calculated. Chi-square test, Independent t-test, one-way ANOVA with post hoc analysis using Tukey’s test, Pearson’s correlation test, and stepwise multiple linear regressions were used for inferential statistics.
RESULTS
There were 661 respondents to our study, and all responses were complete. The majority of our respondents were in the age group of 18–29 years and <8% representation above 42 years. 53.3% of our respondents were male, from an urban background (81.1%), completed professional courses (77%), married (50.4%), and employed fulltime (63.5%). Around 42% of our respondents earned more than Rs. 40,000 monthly. There was a significant difference in the occurrence of higher nomophobia scores among age groups and marital status categories [Table 1].
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Table 1: Sociodemographic data and its relation to smartphone dependency
All of our respondents owned a smartphone and the majority of them owned 4G smart phones (82.5%). Approximately 59% of our respondents consumed more than 4 GB data/month which skewed from 200MB to 90GB. Around 42% of our respondents spent more than 4 h on smart phones every day on activities not related to work. Our participants spent as low as Rs. 20 to as high as Rs. 10,000 with a median monthly expense of 350 rupees. The median age at which the participants started using mobile phones and smartphone were 19 (4–59) and 24 (6–65) years, respectively. The median nomophobia scores obtained were 77 (±22.5) with a range of 20–140. Among the participants, 326 (49.3%) had scored above the median cutoff score [Table 2].
Table 2: Descriptive distribution of smartphone usages among study participants
Figure 1 represents the reason and context of smart phone use among study participants. The majority were using to look for information on the Internet, followed by talking and texting to family members and friends, checking E-mails and social media. Similarly most of them used smartphone in situations when they feel bored, alone or waiting for something or someone.
Figure 1: Reason and context of smartphone use all respondents (n = 661). The sum of variables is more than 100% because participants could give multiple responses within the same category
Figures 2-4 represent reasons and context of smartphone use with respect to gender, age group and occupation respectively. There were significant differences (P < 0.05) observed between genders in the following categories in reasons and context (i.e.) checking E-mails, using as planners, while waiting for someone, as soon as waking up, when using public transport, use sacrificing sleep and during classrooms or in meetings. Significant differences (P < 0.05) were also observed in occupation categories for reasons and context of smart phone use in checking E-mails, gaming listening to music, seeking information on the internet, use as planners for events/meetings, while waiting for someone, when using public transport and during classrooms or in meetings. There were significant differences (P < 0.05) observed between age group in the following categories (i.e.) Checking social media, gaming, listening to music, looking for information on the internet, when bored when using public transport and during classrooms or in meetings.
Figure 2: Number of male respondents=352, Number of female respondents=309. The sum of variables is more than 100% because participants could give multiple responses within the same category
Figure 3: Number of respondents aged <30 year = 338, Number of respondents aged ≥30 year = 323. The sum of variables is more than 100% because participants could give multiple responses within the same category
Figure 4: Number respondents who were Employed = 408; Student = 160; others viz., homemakers, not employed or retired = 93. The sum of variables is more than 100% because participants could give multiple responses within the same category
Our respondents scored a higher median score of 6 on Q2 (annoyed if I could not look up information on smartphone when needed) and Q6 (worried because family and friends couldn’t reach me) and a lower median score of 2 on Q3, Q6, Q8, Q16, Q17, Q18, Q20 (unable to get news, run out of data or credit, disconnected from online identity, stay up-to-date with social media, check notification or updates, not know what to do). One-way ANOVA measures reported a significant difference in nomophobia scores between age groups, with participants between 18 and 29 years scoring higher than 30 and 41 years and the difference was significant at a P = 0.005. There was no significant difference (P > 0.05) in nomophobia scores between genders (t-test) and occupations (one way ANOVA) as described in Table 3.
Table 3: Comparison of nomophobia scores within the age group, gender and occupation
Among the domains of NMPQ, students scored significantly higher than the employed group in not able to communicate (P = 0.019) and losing connectedness (P = 0.035) domain. Gender differences were noted with males scoring higher than females in losing connectedness (P = 0.011), not able to communicate (P = 0.033) and giving up convenience (P = 0.002) domains. Participants of age 18–29 years scored higher than 30–41 years group in losing connectedness domain (P = 0.01). Age groups 18–29 and 30–41 years both scored significantly higher than 54–65 years group participants in not being able to access information domain with the P values of 0.005 and 0.041 respectively.
On Pearson’s correlation analysis nomophobia scores correlated positively with duration of smartphone use per day (r = 0.284; P < 0.001) and inversely with starting age of using mobile phones (r = 0.153; P < 0.001). On step-wise multiple linear regression models only hours of smartphone use per day significantly predicated nomophobia scores, with a regression model equals to 80.34 + 4.91 h of smartphone use per day. Details of other models described in Table 4.
Table 4: Stepwise multiple linear regression model
DISCUSSION
The participants scoring above the median was 49.3%, a finding similar to that reported from Pondicherry.[3] Those scoring above 100 points was 16.8% which was lower compared to those reported earlier from India and other countries.[11–13] There seems to be an inverse association between age and nomophobia, a finding reinforced by the significant difference observed between age 18–29 and 30–41 years age group indicating higher dependency in young. Our study reported a higher nomophobia scores. As the study was conducted during the period of free data offer by a private network provider, this could have contributed to the transition in the prevalence of higher nomophobia scores. Similarly, the difference could be explained by the inclusion of respondents across age groups. The above factors could possibly explain our finding of around 6% participants scoring above median cut-off scores among those aged above 40 years in our study as compared to other study reporting as low as 2.3%.[6]
We did not find any significant association between gender and nomophobia a finding similar to that reported in a study.[6] But contrast to the findings from other studies.[3,14–16] Our study however observed gender differences in the 3 out of 4 subdomains scores. Though the inference was similar to the study by Kanmani et al.[6] the prevalence reported differed slightly with a higher percentage reported higher nomophobia scores in our study. Similar findings were observed on comparing occupation categories to the results of the findings from the study mentioned earlier.[6] It was evident in our study too that college students seem to fall under marginally higher levels of nomophobia which may be attributed to more availability of leisure time, lesser responsibility, the curiosity of exploring technology and extensive usage for educational or research purposes.[6]
Looking for information on the internet, texting, talking, checking social media and E-mails were the most commonly reported use.[5,7,17–19] As in our study. Being alone and bored or waiting for someone seem to be the frequent context of smartphone use among participants similar to that reported by Dasgupta et al.[5] With 42% of respondents using a smartphone for more than 4 h/day, the duration of smartphone use becomes a significant predictor of nomophobia in our study. This finding was similar to other studies from India,[5,20] Pakistan[17] and Korea.[19] These findings suggested that longer duration and more frequent use of smartphones increased the risk for nomophobia.
Strengths and limitations
Most of the studies on nomophobia till date had focused mainly on student population, our study attempted to look for difference across age group and among working persons too. Our study used a median cut-off score for categorization of nomophobia to avoid over diagnosis of it and to account for normative behavior without significant dysfunction.
Inherent to the study design the study population may not be clearly defined, the response rate could not be measured, information about nonresponders could not be gathered, hence selection bias could not be assessed, though our questionnaire was designed to be anonymous, privacy issues pertaining to the medium of data collection prevails.[21] Socially desirable responses from participants could not be ruled out. No tracking of smartphone use to corroborate with self-reported responses was carried out in this study. Inclusion of the individuals not using smartphone would have provided the actual prevalence of nomophobia among all mobile-phone users which is beyond the scope of this study.[22] The above factors needed to be considered before generalizing the results.
CONCLUSION
The prevalence of nomophobia remains high in our study. Younger age and higher duration of smartphone use had a positive association with nomophobia with the duration of smartphone use per day emerging as a significant predictor of nomophobia. This study adds to the existing evidence on nomophobia with additional details on differences across age groups. Future studies carried out with robust sampling techniques will help us understand the pattern of nomophobia distribution and help us develop specific intervention strategies.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
Acknowledgements
The authors would like to thank all the participants of the survey for their time and honest responses.
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