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Article

Perceived Health and Nomophobia among Young Adults: The Mediating Role of Depression and Stress

1
Department of Public and Community Health, School of Public Health, University of West Attica, 12243 Athens, Greece
2
Department of Fisheries and Aquaculture, School of Agricultural Sciences, University of Patras, 30200 Messolonghi, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(1), 96; https://doi.org/10.3390/su16010096
Submission received: 30 November 2023 / Revised: 17 December 2023 / Accepted: 19 December 2023 / Published: 21 December 2023
(This article belongs to the Section Health, Well-Being and Sustainability)

Abstract

:
Nomophobia refers to the contemporary fear of being unable to communicate sufficiently via a smartphone. As reported in the literature, nomophobia leads to excessive smartphone use, and one of the crucial issues of this overuse is its effect on physical and mental health. The current study aimed to investigate the association between perceived health assessments and nomophobia among young adult smartphone users through the mediating role of depression and stress. A cross-sectional study was conducted on 1408 young adults aged 18–25 in Athens, the capital city of Greece. Data were collected through a self-reported questionnaire and included information on sociodemographic characteristics, patterns of smartphone use, self-perceived health status, and depressive and stress symptoms. Nomophobia was assessed using the “Nomophobia Questionnaire (NMP-Q)”. The effect of nomophobia on perceived health was analyzed by taking into account its effect on depression and stress. The results indicate a positive significant association between nomophobia and overall health burdening (i.e., musculoskeletal, hearing/vision, and psychosomatic symptoms). Depression and stress seem to play a significant mediating role in this association. Raising awareness through health-promoting interventions could play a pivotal role in eliminating the phenomenon of nomophobia and its consequences.

1. Introduction

In contemporary society, communication and information technologies, particularly smartphones, have become inseparable aspects of daily life. Smartphones have transcended from their traditional role as mere mobile phones into being essential tools in recent generations, particularly among youths [1]. They have revolutionized interpersonal communication, overcoming temporal and geographical constraints. Moreover, smartphones empower young individuals to manage a wide range of daily activities through a single device, including socializing, texting, email checking, web browsing, shopping, gaming, and entertainment [2]. Despite the fact that they have considerable potential benefits, excessive and uncontrolled smartphone use can have various side effects, including patterns of excessive behavior [3]. A recent study highlighted that excessive smartphone use may pose health risks to individuals [4].
Nomophobia represents a relatively recent phenomenon denoting an excessive reliance on smartphones. This term, derived from “NO-MObile-PHOne phoBIA”, signifies the fear of losing or being without one’s smartphone [5]. Nomophobia encompasses the anxiety, fear, and discomfort that arise from losing the ability to communicate with others, i.e., due to smartphone loss or Internet disruptions, particularly for individuals habituated to these devices [2]. Multiple research studies have aimed to establish the prevalence of nomophobia. In a recent systematic review study, the prevalence of nomophobia ranged from 15.2% to 99.7% of the participants, with variations based on age, gender, daily smartphone use duration, and years of smartphone ownership. It was also observed that young adults exhibit a higher susceptibility to nomophobia in comparison to individuals from other age groups [6], while it is also noted that nomophobia exerts detrimental impacts on the physical and psychological well-being of young adults [7].
In a study conducted in India, it was revealed that 73% of students exhibited symptoms of nomophobia, while the most prevalent adverse effects, reported by 61% of the study sample, were headaches and lethargy, potentially attributed to excessive smartphone use [8]. Moreover, the results of another study in India with 774 undergraduate students as participants revealed that 20.8% had mild nomophobia, 54.5% had moderate nomophobia, and 23.5% had severe nomophobia. Approximately 25% of the participants mentioned experiencing health-related issues due to prolonged smartphone use. Nomophobic individuals exhibited health symptoms such as headaches, eye strain, and fatigue, which were the most frequently reported symptoms in the study [9]. In the same line, similar studies have shown an association among nomophobia and adverse health effects, with most common symptoms been headaches [10,11,12], thumb ache [12], eye strain [10,12], fatigue [10], sleeping difficulty [13], and disturbance of sleep [10,11].
The results of a study in Seoul highlighted the relationship between smartphone use and musculoskeletal symptoms, with mainly the shoulders and neck being the most discomforting areas. Additionally, it was observed that individuals’ back pain exhibited a positive correlation with the size of their smartphone’s screen [14]. According to a preliminary study of a Canadian university population, it was revealed that 98% of participants were smartphone users, while 84% experienced pain in at least one part of their body. The most prevalent discomfort was observed in the base of the thumb in both hands [15].
Apart from musculoskeletal symptoms, smartphone overuse also demonstrated a significant impact on visual symptoms in the Seoul study. These symptoms included eye strain, eye fatigue, and dry eyes. The proximity of smartphone screens to eyes during their use might explain this association with visual symptoms, particularly when the duration and intensity of smartphone use was extensive [16]. Similarly, a high percentage of the respondents mentioned sleep disturbances and eye strain (38.3% and 34.4%, respectively), while the less frequently reported symptoms comprised shoulder/neck/back pain (18.1%), headaches (17.8%), watering of the eyes (12%), fatigue (10.8%), and wrist pain (10.5%) due to prolonged smartphone use [17]. Additionally, smartphone addiction has been linked to issues such as poor sleep quality, fatigue, difficulties in sleep, and shortened sleep duration [18,19].
Several investigations among university students have demonstrated a significant positive association between depression and anxiety and nomophobia levels [8,20,21], while in other studies, nomophobia and smartphone overuse were identified as predictors for depression and anxiety [22,23,24]. This outcome indicates the potential impact of nomophobia, arising from frequent and uncontrollable smartphone use, on the participants’ psychological well-being [20]. In the same direction, other relevant investigations indicated frequent smartphone use as a potentially problematic behavior, associated with the negative induction of stress, anxiety, and symptoms of depression [18,25,26,27]. A recent systematic review showed an association between problematic smartphone use and adverse mental health symptoms such as depression, anxiety, high stress levels, and impaired sleep quality [28]. In addition, the results of one cross-sectional study showed that high levels of nomophobia were positively related to increased levels of stress, depression, and anxiety [29].
Additionally, depression has been associated with several health issues (i.e., persistent joint and limb pain, back pain and gastrointestinal issues, fatigue and sleep disturbances) [30]. A study conducted in Norway noted that participants with an elevated score in depressive symptoms were at a higher risk of experiencing neck and shoulder pain [31].
Smartphones occupy a significant role in people’s lives, particularly among the youngest generations, who are thus more vulnerable to nomophobia. In addition, even though there has been growing attention on nomophobia among young adults, globally, there is scarce evidence regarding its relation to health. Thus, the research questions of this study aimed to address the possible association between nomophobia and the health status of participants. Additionally, the relationship of nomophobia with perceived health was evaluated through the potential mediating effect of depression and stress.

2. Materials and Methods

2.1. Participants and Procedure

The current cross-sectional study included 1408 male and female students aged 18 to 25 years from six faculties at the University of West Attica and Post-Secondary Vocational Training institutions located in Athens, the capital metropolitan area of Greece. This certain university ranks as the third largest in Greece based on student population. The selection process adhered strictly to predefined criteria, which included owning a smartphone, falling within the 18 to 25 age range, and completing the informed consent form. The mean age of the participants was 20.7 years (SD = 2.0 years); 71.7% were women, 68.5% were non-employees, and 74.2% were living with their parents.
Data collection involved the distribution of an online self-administered questionnaire. An informed consent form was requested before filling out the study questionnaire. The questionnaire was developed using the Google Forms application, for which the relevant web link was provided through the e-class platform of the courses during the 2020–2021 academic year. The topics of these courses were not connected to the study and participation was voluntary without any benefits or penalties. Due to COVID-19 social distancing measures, the study’s researcher informed the participants about the aim of the study via the Microsoft Teams platform and ensured that all necessary information was available and accessible during the questionnaire’s completion. The response rate was sufficiently high, reaching almost the total number of the students surveyed.
Ethical approval for the study was obtained from the University of West Attica’s research committee (approval number: 14/21-09-2020) and adhered to the ethical guidelines established in the Declaration of Helsinki (1964) and its subsequent revisions. Participants received detailed information about the study’s objectives and methodology and their participation was entirely voluntary and depended on their informed consent.

2.2. Measures

The questionnaire consisted of five separate sections, covering the following areas: (a) socio-demographic characteristics (i.e., age, gender, educational attainment, place of residence, and parental educational background); (b) patterns of smartphone use, comprising parameters like daily use duration, smartphone use purpose, and frequency of calls and text messages; (c) perceived health questionnaire (musculoskeletal, hearing/vision, and psychosomatic symptoms); (d) the Nomophobia Questionnaire (NMP-Q); and (e) the Depression Anxiety Stress Scale-21 (DASS-21).

2.2.1. Nomophobia Questionnaire (NMP-Q)

The Nomophobia Questionnaire (NMP-Q) comprises 20 Likert scale items, rated on a 7-point scale from 1 (‘strongly disagree’) to 7 (‘strongly agree’). Scores are calculated by summing the responses, resulting in a range from 20 to 140. Higher scores (140) indicate severe nomophobia, while 20 suggests no nomophobia. Scores in the range of 21–59 indicate mild nomophobia, 60–99 denote moderate nomophobia, and 100–140 signify severe nomophobia. The questionnaire assesses four dimensions: (a) not being able to communicate, (b) losing connectedness, (c) not being able to access information, and (d) giving up convenience. The questionnaire was originally developed by Yildirim and Correia (2015) [2] and was subsequently adapted and validated for the Greek language. Exploratory and confirmatory factor analyses of our Greek version confirmed that the four-factor structure was consistent with the original model. An overall nomophobia scale was derived by combining all NMP-Q items [32]. This total scale exhibited strong internal consistency, with Cronbach’s alpha coefficients of 0.945 for both questionnaire versions. Additionally, the Cronbach’s alpha values for each factor were: (a) 0.936, (b) 0.895, (c) 0.867, and (d) 0.854, closely resembling the original NMP-Q values of 0.939, 0.827, 0.819, and 0.874, respectively.

2.2.2. Depression Anxiety Stress Scale-21 (DASS-21)

Depression, anxiety, and stress levels were assessed through the DASS-21 scale. This scale’s structure includes three distinct subscales intended for self-evaluation of adverse emotional states associated with depression, anxiety, and stress, using a 4-point Likert-type scale [33]. The total values of the subscales are classified into normal, mild, moderate, severe, and extremely severe categories. The Cronbach’s alpha values of the studied subscales were 0.90, 0.88, and 0.88 for depression, anxiety, and stress, respectively, suggesting their high internal consistency.

2.2.3. Perceived Health Questionnaire

The questions regarding perceived health were based on relevant research from the literature. They were divided into three parts: (a) musculoskeletal symptoms, including questions such as, “do you feel pain in the neck?”, “do you feel pain in the spine?”, “do you feel pain in the thumb?”; (b) hearing and visual symptoms, consisting of questions such as “have you noticed a problem with your hearing?”, “do you feel blurry vision?”, “do you experience dry eyes?”; and (c) psychosomatic symptoms, incorporating questions like “do you have headaches?”, “do you feel tachycardia?”, “do you have disturbances during nighttime sleep?”, “do you feel fatigue?”. The questionnaire consists of 18 Likert scale items, rated on a 5-point scale from 0 (never) to 4 (very often). Scores are calculated by summing the responses, resulting in a range from 0 to 72.

2.3. Statistical Analysis

Data analytics for the quantitative variables was performed through measures of central tendency, such as the mean value and standard deviation, while for the categorical and ordinal variables we used the means of their absolute and relative frequencies. T tests and analyses of variance for linear trends were used in univariate procedures. Multiple linear regression models with mediation analysis were used to estimate the association between the nomophobia scale and perceived health status.
In order to quantify the participants’ perceived health, three new variables were calculated by summing the individual values of the health questions. These three composite variables were defined by groups of symptoms corresponding to musculoskeletal, hearing/visual, and psychosomatic problems. In addition, an overall scale of the perceived health status results was constructed by summing the composite health variables. The values of these four new health scales (total, musculoskeletal, hearing/vision, and psychosomatic) define the perceived health burden, with high values corresponding to a worse health status. In addition, a new variable was constructed measuring the total phone usage times of the participants by multiplying the length of time that the mobile phone has been owned by its daily use.
Both the nomophobia and perceived health variables were homogenized to 100-point scales so that relative changes in one compared to the other were reported as percentages. This was deemed necessary in order to make the interpretation of the regression models easier to understand.
Four regression models were run with the total health burdening scale and individual subscales as dependent variables. The sociodemographic data of the participants were used as covariates in the model, while the depression and stress variables were introduced as mediators. Taking into account its effect on depression and stress, the direct and indirect effects of nomophobia on the perceived health burdening scales were estimated. All statistical calculations were performed using SPSS version 28 statistical software (SPSS Inc., IBM Corp, Armong, NY, USA). The mediation effects were estimated and tested using the PROCESS macro for SPSS [34], with 5000 bootstrapping samples.

3. Results

About 19% of participants experienced severe nomophobia, and their reported health problems scaled up in line with these levels of nomophobia. The highest mean value of the total health burdening scale, 32.7, was observed among participants with severe nomophobia, while the mean values of those with moderate and mild nomophobia were 28.1 and 20.1, respectively. The subscale health indicators showed similar scores. Psychosomatics had the highest mean values at all levels of nomophobia (39.6, 33.1, and 24.3 for severe, moderate, and mild nomophobia, respectively), followed by musculoskeletal and hearing/vision problems (all linear trend p values < 0.001). Similar linear relationships appeared between depression and stress with the health burden indicators. The reported health problems scaled up proportionally with the levels of depression and stress. People with greater levels of depression/stress tended to report greater health problems (all linear trend p values < 0.001). Regarding the sociodemographic data of participants, women reported worse health statuses in all health scales compared to men (all p values < 0.001), the 18–20 age group was found to be more prone to psychosomatic symptoms, and working participants complained more of musculoskeletal discomforts (p value < 0.05) (Table 1).
Table 2 and Table 3 show the results of the regression and mediation analyses. Four regression models were run with the perceived health scales as outcome variables and total nomophobia score as predictors. Gender, age group, working status (yes, no), residency (alone, with parents), and total phone usage time (the amount of years spent owning the phone multiplied by the daily mean phone use) were entered as covariates. In these analyses, the health and nomophobia variables were proportionally transformed into 100-point scales. This allowed the regression coefficients to relate the percent changes in the health scales to corresponding percent changes in the nomophobia scores. In all regression models, the effect of nomophobia on the perceived health burdening was significant (all p values < 0.001). The greatest effect was observed in the psychosomatic disorders scale. The psychosomatic scale increases by approximately 0.26 percentage points for each percentage point increase in nomophobia. This practically means that about 26% of the increase in the psychosomatic scale was associated with nomophobia. Similar changes link nomophobia with the other health scales. The burden of the overall perceived health was affected by nomophobia by about 22%. For the health indicators of musculoskeletal and hearing/visual problems, the burdens were approximately 22% and 17%, respectively (Table 2).
The aforementioned total effect models were tested through the PROCESS macro for assessing the possible mediation effect of depression and stress. Based on 5000 bootstrap samples, confidence intervals for the indirect effect of depression and stress were constructed. From this analysis, we found that a significant part of nomophobia’s impact on perceived health was due to the mediating effect of depression and stress. All of the possible indirect effects of depression and stress were significant since 95% CI did not cross zero. Moreover, the size of the mediation effect (i.e., the proportion of the variance in outcomes that can be explained by the indirect effect) is Radj2 = 0.23 for the overall health index, and 0.14, 0.13, and 0.31 for the musculoskeletal, hearing/vision, and psychosomatic indices, respectively (all corresponding p values < 0.001). Furthermore, in all regression analyses, the importance of nomophobia’s effect on health indicators remained statistically significant. This means that depression and stress partially mediate the relationship between nomophobia and perceived health (Table 3).
The mediation analysis of the overall health index showed that the indirect effects of depression and stress are 0.03 (95% CI: 0.01–0.04) and 0.09 (95% CI: 0.07–0.12), respectively. The total indirect effect is 0.12 (95% CI: 0.09–0.15). Therefore, a significant part of the total effect of nomophobia on perceived health (0.12 out of 0.22) is linked to stress and depression. Similar indirect effects were also identified in the mediation models of individual health indicators. In all analyses, the mediation of stress and depression is partial, and the effect of nomophobia remains significant. The largest indirect effects appeared in the psychosomatic model. Here, the indirect effects of depression/stress were greater than in all other health indices. The mediating effect of depression is 0.04 (95% CI: 0.02–0.06) and the mediating effect of stress is 0.14 (95% CI: 0.11–0.18), and their total effect was 0.18 (95% CI: 0.1–0.22). In the mediation models of musculoskeletal and hearing/visual problems, the indirect effects were slightly smaller. The total indirect effects of depression/stress on musculoskeletal and hearing/visual problems were both equal to 0.10 (95% CI: 0.08–0.13).
Regarding the socio-demographic variables, the mediation models showed that significant differences in all perceived health variables appeared between the two sexes and between those who work and those who were unemployed. Women complained to a greater extent than men regarding all kinds of health problems, with the average differences in the respective variables ranging from 3 (95% CI: 0.11–0.18) in hearing/visual problems to 4 (95% CI: 2.01–5.99) percentage points in musculoskeletal problems. Also, those who work reported a higher burden on their health, from 2.14 (95% CI: 0.03–4.25) in psychosomatic problems to 3.93 (95% CI: 1.95–5.91) percentage points in musculoskeletal problems (Table 3).
Since extensive smartphone use is associated with several adverse health effects, an additional analysis was performed to explore this association. The more often participants were checking their phone (i.e., up to 10 min) and the more hours/day they spent using it (i.e., more than 10 h/day), the more often they reported musculoskeletal, hearing/vision, and psychosomatic complications (all p values < 0.05). The reasons for their smartphone overuse (i.e., calls and messages) or their number of friends and followers did not seem to have any impact on health issues (Table 4).

4. Discussion

The overuse of smartphone devices influences both one’s lifestyle and health, giving rise to the phenomenon of nomophobia. The latter, in turn, has a significant impact on an individual’s physical and psychological well-being [4,6]. The results of the present study revealed a positive association between nomophobia and an adverse health status, both direct and mediated through the effect of nomophobia on stress and depression. Specifically, it was observed that participants with a severe level of nomophobia were more prone to exhibit musculoskeletal, hearing/vision, and psychosomatic symptoms compared to those with mild and moderate levels. This result is in accordance with an exploratory study of nomophobia in India, where it was shown that most of the participants reported various physical discomforts, including eye strain, watering of eye, fatigue, headaches, sleep disturbances, wrist pain, as well as pain in the shoulder, neck, and back regions. The incidence of physical symptoms was significantly higher among participants exhibiting nomophobia compared to their counterparts who did not manifest severe levels of nomophobia [10]. Furthermore, similar studies have shown a link between nomophobia and health-related issues, with the most prevalent adverse effects being headaches [8,9,11,12], thumb ache [12], lethargy [8], eye strain [9,12], fatigue [9], sleeping difficulty [13], disturbance of sleep [11], lack of sleep [12].
The impact of nomophobia on individuals’ perceived health burdens was significant, with the most pronounced effect being observed in psychosomatic problems. Women generally reported a higher prevalence of health issues in all categories than men. A survey conducted in Pakistan among university students similarly showed that neck pain was more frequently cited by females than by males [35]. Moreover, in a previous relevant investigation among Norwegian adolescents, girls reported neck and shoulder pain to a greater extent than boys [31]. In the present study, it was revealed that working students mentioned a greater health burden in relation to psychosomatic and musculoskeletal problems compared to non-working ones. In this line, the findings from a research study among smartphone users in Slovenia confirmed that working university students compared to non-working ones experienced the highest rates of musculoskeletal symptoms, with back, neck, and shoulder pain being the most frequent [36].
Moreover, the reported health burdening in the present study was positively associated with increasing depression and stress; participants identified with higher levels of depression and stress tended to perceive greater health burdening. Additionally, it is documented in the literature that individuals exhibiting depressive symptoms exhibited adverse health effects such as persistent joint and limb pain, back pain, gastrointestinal concerns, fatigue, and sleep disturbances [30,37,38]. In the Norwegian adolescent study mentioned earlier, it was observed that participants with elevated scores of depressive symptoms were at the greatest risk of experiencing neck and shoulder pain [12]. As indicated in the literature, individuals who excessively use smartphones tend to display higher levels of depression, whereas a more appropriate usage is associated with lower levels of depression, anxiety, and stress [26,29]. This suggests a notable relation between smartphone use and mental well-being [39,40].
Furthermore, our mediation analysis revealed that a substantial part of nomophobia’s influence on perceived health was attributable to the indirect effects of depression and stress. Even though the mediation of stress and depression was partial, the influence of nomophobia remained significant, with the most substantial indirect effect manifesting in the psychosomatic model. To the best of our knowledge, there is a lack of evidence regarding the above findings among young adults. Thus, this is the first study which highlights the impact of nomophobia on individuals’ perceived health burden with the mediating role of depression and stress. However, a study conducted among an adolescent population in Korea demonstrated that depressive symptoms were considered as a mediator in the relationship between problematic smartphone use and psychosomatic disorders [27].
Finally, the present study’s results show that participants who checked their smartphone more frequently and spent more hours on it per day reported health issues more often. Findings of a recent study indicated that 33.2% of the respondents checked their smartphones every 10–20 min [41], while 31% of the participants in another study stated that they checked their smartphone every 10 min [42]. Nevertheless, in both studies, there was no association found between smartphone checking and any musculoskeletal, hearing/vision, or psychosomatic symptoms. Conversely, college students complained about several health issues arising from persistent stress due to continuous smartphone use, with the most frequent being headaches, neck and limb pains, backaches, as well as redness in their eyes and tinnitus in their ears on several days [43,44]. According to a previous study in a Canadian university population, it was revealed that 98% of participants were smartphone users, while 84% experienced pain in at least one part of their body while the most prevalent discomfort was observed in the base of the thumb in both hands. Moreover, a significant relation between the average duration of smartphone use (>3.5 h/day) and the existence of pain in the left shoulder, right shoulder, and neck was also demonstrated [11]. Thus, excessive smartphone use may lead to adverse health effects, encompassing dry eyes, computer vision syndrome, neck and shoulder problems, discomfort of the thumb and wrist, as well as sleep disturbances and insomnia [45].
It is also important to mention the significance of Sustainable Development Goal 4 (SDG 4) [46] within the 2030 Agenda for Sustainable Development, which focuses on the substantial augmentation of skills among youth and adults. Specifically, its emphasis is on digital skills, integral to widespread learning facilitated by devices like smartphones [47].

Limitations

Despite the substantial sample size, which ensures sufficient evidence for the relationships established, it is essential to acknowledge the limitations of the present study when interpreting the results. The cross-sectional nature of the data restricts the ability to establish a causal sequence of events. Moreover, this study’s participants were recruited from a single university in Greece, potentially constraining the generalizability of the findings. Furthermore, the reliance on self-reported information without medical confirmation poses another limitation. However, it is worth noting that certain questions were retrieved from a wide range of scientific papers. While the use of self-reported information presents a limitation, the significance of such data should not be underestimated.

5. Conclusions

Nomophobia and smartphone overuse were found to be positively associated with health issues among young adults. Depression and stress seemed to play a significant mediating role in this association. Further research is required to thoroughly assess the relationship between nomophobia and the physical and psychological well-being of individuals in relation to depression and stress. Given the broad adoption of smartphones as prevalent instruments for information and communication, it becomes imperative to examine potential challenges associated with their usage (i.e., mental, physical, and social health), particularly among youth. Therefore, the appropriate use of smartphones should play a fundamental role in cultivating a more proficient and astute society, which will contribute to achieving more sustainable development for humanity. Raising awareness through health promotion interventions could play a pivotal role in eliminating the phenomenon of nomophobia. The current study underscores the imperative need for further research in this area.

Author Contributions

Conceptualization, V.N., C.G. and E.V.; methodology, C.G., V.N. and E.V.; software, C.G.; formal analysis, C.G.; investigation, E.V.; data curation, E.V.; writing—original draft preparation, E.V.; writing—review and editing, E.V., C.G. and V.N.; supervision, C.G., V.N. and A.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was authorized by the University of West Attica’s research committee (14/21-09-2020) and was conducted in compliance with the Declaration of Helsinki (1989).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to certain restrictions (e.g., for privacy or ethical reasons).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Daei, A.; Ashrafi-rizi, H.; Soleymani, M.R. Nomophobia and health hazards: Smart phone use and addiction among university students. Int. J. Sci. Res. 2019, 10, 202. [Google Scholar] [CrossRef]
  2. Yildirim, C.; Correia, A.P. Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Comput. Hum. Behav. 2015, 49, 130–137. [Google Scholar] [CrossRef]
  3. Servidio, R. Self-control and problematic smartphone use among Italian University students: The mediating role of the fear of missing out and of smartphone use patterns. Curr. Psychol. 2021, 40, 4101–4111. [Google Scholar] [CrossRef]
  4. Goncalves, S.; Dias, P.; Correia, A.P. Nomophobia and lifestyle: Smartphone use and its relationship to psychopathologies. Comput. Hum. Behav. Rep. 2020, 2, 100025. [Google Scholar] [CrossRef]
  5. King, A.L.S.; Valenca, A.M.; Silva, A.C.O.; Baczynski, T.; Carvalho, M.R.; Nardi, A.E. Nomophobia: Dependency on virtual environments or social phobia? Comput. Human Behav. 2013, 29, 140–144. [Google Scholar] [CrossRef]
  6. Notara, V.; Vagka, E.; Gnardellis, C.; Lagiou, A. The Emerging Phenomenon of Nomophobia in Young Adults: A Systematic Review Study. Addict Health 2021, 13, 120–136. [Google Scholar] [CrossRef] [PubMed]
  7. Galhardo, A.; Loureiro, D.; Raimundo, E.; Massano-Cardoso, I.; Cunha, M. Assessing nomophobia: Validation study of the European Portuguese version of the Nomophobia Questionnaire. Commun. Ment. Health J. 2020, 56, 1521–1530. [Google Scholar] [CrossRef]
  8. Sharma, N.; Sharma, P.; Sharma, N.; Wavare, R.R. Rising concern of nomophobia amongst Indian medical students. Int. J. Res. Med. Sci. 2015, 3, 705–707. [Google Scholar] [CrossRef]
  9. Jilisha, G.; Venkatachalam, J.; Menon, V.; Olickal, J.J. Nomophobia: A mixed-methods study on prevalence, associated factors, and perception among college students in Puducherry, India. Indian J. Psychol. Med. 2019, 41, 541–548. [Google Scholar] [CrossRef]
  10. Chandak, P.; Singh, D.; Faye, A.; Gawande, S.; Tadke, R.; Kirpekar, V.; Bhave, S. An Exploratory Study of Nomophobia in Post Graduate Residents of a Teaching Hospital in Central India. Int. J. Indian Psychol. 2017, 4, 48–56. [Google Scholar] [CrossRef]
  11. Myakal, V.V.; Vedpathak, V.L. Nomophobia—Mobile phone dependence, a study among students of a rural medical college. Int. J. Community Med. Public Health 2019, 6, 2034–2040. [Google Scholar] [CrossRef]
  12. Dongre, A.S.; Inamdar, I.F.; Gattani, P.L. Nomophobia: A Study to Evaluate Mobile Phone Dependence and Impact of Cell Phone on Health. Natl. J. Community Med. 2017, 8, 688–693. [Google Scholar]
  13. Veerapu, N.; Baer Philip, R.K.; Vasireddy, H.; Gurrala, S.; Kanna, S.T. A study on nomophobia and its correlation with sleeping difficulty and anxiety among medical students in a medical college, Telangana. Int. J. Community Med. Public Health 2019, 6, 2074–2076. [Google Scholar] [CrossRef]
  14. Kim, H.J.; Kim, J.S. The relationship between smartphone use and subjective musculoskeletal symptoms and university students. J. Phys. Ther. Sci. 2015, 27, 575–579. [Google Scholar] [CrossRef] [PubMed]
  15. Berolo, S.; Wells, R.P.; Amick, B.C., 3rd. Musculoskeletal symptoms among mobile hand-held device users and their relationship to device use: A preliminary study in a Canadian university population. Appl. Ergon. 2011, 42, 371–378. [Google Scholar] [CrossRef] [PubMed]
  16. Toh, S.H.; Coenen, P.; Howie, E.K.; Mukherjee, S.; Mackey, D.A.; Straker, L.M. Mobile Touch Screen Device Use and Associations with Musculoskeletal Symptoms and Visual Health in a Nationally Representative Sample of Singaporean Adolescents. Ergonomics 2019, 62, 778–793. [Google Scholar] [CrossRef] [PubMed]
  17. Khilnani, A.K.; Thaddanee, R.; Khilnani, G. Prevalence of nomophobia and factors associated with it: A cross-sectional study. Int. J. Res. Med. Sci. 2019, 7, 468–472. [Google Scholar] [CrossRef]
  18. Thomée, S.; Härenstam, A.; Hagberg, M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults—A prospective cohort study. BMC Public Health 2011, 11, 66. [Google Scholar] [CrossRef]
  19. Yang, J.; Fu, X.; Liao, X.; Li, Y. Association of problematic smartphone use with poor sleep quality, depression, and anxiety: A systematic review and meta-analysis. Psychiatry Res. 2020, 284, 112686. [Google Scholar] [CrossRef]
  20. Bhattathirippad, S.; Patel, N.M. Social Networking Usage, Nomophobia and Depression Symptoms among Young Adults. Int. J. Indian Psychol. 2021, 9, 570–584. [Google Scholar] [CrossRef]
  21. Augner, C.; Hacker, G.W. Associations between problematic mobile phone use and psychological parameters in young adults. Int. J. Public Health 2012, 57, 437–441. [Google Scholar] [CrossRef] [PubMed]
  22. Çakmak Tolan, Ö.; Karahan, S. The relationship between nomophobia and depression, anxiety and stress levels of university students. Int. J. Psychol. Educ. Stu. 2022, 9, 115–129. [Google Scholar] [CrossRef]
  23. Bae, E.J.; Kim, D.E.; Sagong, H.; Yoon, J.Y. Problematic smartphone use and functional somatic symptoms among adolescents: Mediating roles of depressive symptoms and peer relationships by gender. Arch. Psychiatr. Nurs. 2022, 40, 25–31. [Google Scholar] [CrossRef] [PubMed]
  24. Green, M.; Kovacova, M.; Valaskova, K. Smartphone addiction risk, depression psychopathology, and social anxiety. Anal. Metaphys. 2020, 19, 52–58. [Google Scholar] [CrossRef]
  25. Kliestik, T.; Scott, J.; Musa, H.; Suler, P. Addictive smartphone behavior, anxiety symptom severity, and depressive stress. Anal. Metaphys. 2020, 19, 45–51. [Google Scholar] [CrossRef]
  26. Demirci, K.; Akgönül, M.; Akpinar, A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J. Behav. Addict. 2015, 4, 85–92. [Google Scholar] [CrossRef] [PubMed]
  27. Kubrusly, M.; Silva, P.G.; de Vasconcelos, B.; de Leite, G.V.; Santos, E.D.L.G.; de Rocha, P. Nomophobia among medical students and its association with depression, anxiety, stress and academic performance. Rev. Bras. Educ. Médica. 2021, 45, 162. [Google Scholar] [CrossRef]
  28. Sohn, S.; Rees, P.; Wildridge, B.; Kalk, N.J.; Carter, B. Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: A systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry 2019, 19, 356. [Google Scholar] [CrossRef]
  29. Gnardellis, C.; Vagka, E.; Lagiou, A.; Notara, V. Nomophobia and Its Association with Depression, Anxiety and Stress (DASS Scale), among Young Adults in Greece. Eur. J. Investig. Health Psychol. Educ. 2023, 13, 2765–2778. [Google Scholar] [CrossRef]
  30. Trivedi, M.H. The link between depression and physical symptoms. Prim. Care Companion J. Clin. Psychiatry 2004, 6, 12–16. [Google Scholar]
  31. Myrtveit, S.M.; Sivertsen, B.; Skogen, J.C.; Frostholm, L.; Stormark, K.M.; Hysing, M. Adolescent neck and shoulder pain–the association with depression, physical activity, screen-based activities, and use of health care services. J. Adolesc. Health 2014, 55, 366–372. [Google Scholar] [CrossRef] [PubMed]
  32. Gnardellis, C.; Notara, V.; Vagka, E.; Gialamas, V.; Lagiou, A. Validity of the Greek NMP-Q and Sociodemographic Determinants of Nomophobia Among University Students. Int. J. Hum. Comput. Interact. 2022, 39, 842–850. [Google Scholar] [CrossRef]
  33. Lovibond, P.F.; Lovibond, S.H. The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behav. Res. Ther. 1995, 33, 335–343. [Google Scholar] [CrossRef]
  34. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Methodology in the Social Sciences), 2nd ed.; The Guilford Press: New York, NY, USA, 2018. [Google Scholar]
  35. Malik, A.; Pasha, M.U.; Khalid, S.; Ahmad, A.; Gianni, S. Prevalence of neck pain among Undergraduate students of Lahore. Int. J. Sci. Eng. Res. 2017, 8, 569–576. [Google Scholar]
  36. Legan, M.; Zupan, K. Prevalence of mobile device-related musculoskeletal pain among working university students: A cross-sectional study. Int. J. Occup. Saf. Ergon. 2022, 28, 734–742. [Google Scholar] [CrossRef] [PubMed]
  37. Garcia-Cebrian, A.; Gandhi, P.; Demyttenaere, K.; Peveler, R. The association of depression and painful physical symptoms—A review of the European literature. Eur. Psychiatry 2006, 21, 379–388. [Google Scholar] [CrossRef] [PubMed]
  38. Stahl, S. Does depression hurt? J. Clin. Psychiatry 2002, 63, 273–274. [Google Scholar] [CrossRef] [PubMed]
  39. Jo, S.; Baek, I.C.; Fava, M.; Mischoulon, D.; Hong, J.P.; Kim, H.; Park, M.J.; Kim, E.J.; Jeon, H.J. Association of smartphone overuse with depression, anxiety, and other addictive behaviors: A nationwide community sample of Korean adults. Psychiatry Res. 2021, 304, 114133. [Google Scholar] [CrossRef]
  40. Lepp, A.; Barkley, J.E.; Li, J. Motivations and experiential outcomes associated with leisure time cell phone use: Results from two independent studies. Leis Sci. 2017, 39, 144–162. [Google Scholar] [CrossRef]
  41. Rosales-Huamani, J.A.; Guzman-Lopez, R.R.; Aroni-Vilca, E.E.; Matos-Avalos, C.R.; Castillo-Sequera, J.L. Determining Symptomatic Factors of Nomophobia in Peruvian Students from the National University of Engineering. Appl. Sci. 2019, 9, 1814. [Google Scholar] [CrossRef]
  42. Setia, R.; Tiwari, S. A study on NOMOPHOBIA among youth in Indian perspective. Int. J. Indian Psychol. 2021, 9, 688–707. [Google Scholar] [CrossRef]
  43. Acharya, J.P.; Acharya, I.; Waghrey, D. A Study on Some of the Common Health Effects of Cell-Phones amongst College Students. J. Community Med. Health Educ. 2013, 3, 214. [Google Scholar] [CrossRef]
  44. Masthi, N.R. Yashasvini Mobile phone dependence among college students in Bangalore. RGUHS J. Med. Sci. 2012, 2, 84–87. [Google Scholar]
  45. Peraman, R.; Parasuraman, S. Mobile phone mania: Arising global threat in public health. J. Nat. Sci. Biol. Med. 2016, 7, 198–200. [Google Scholar] [CrossRef]
  46. UNESCO. Education 2030. Incheon Declaration and Framework for Action for the Implementation of Sustainable Development Goal 4: Ensure Inclusive and Equitable Quality Education and Promote Lifelong Learning Opportunities for All. Available online: https://bit.ly/38nV17d (accessed on 10 September 2023).
  47. Roig-Vila, R.; Prendes-Espinosa, P.; Urrea-Solano, M. Problematic Smartphone Use in Spanish and Italian University Students. Sustainability 2020, 12, 10255. [Google Scholar] [CrossRef]
Table 1. Perceived health 100-point scales regarding sociodemographic data, nomophobia, and depression and stress categories.
Table 1. Perceived health 100-point scales regarding sociodemographic data, nomophobia, and depression and stress categories.
Total Health Musculoskeletal Hearing/Vision Psychosomatic
N%MeanStd. Dev.p Value *MeanStd. Dev.p Value *MeanStd. Dev.p Value *MeanStd. Dev.p Value *
Nomophobia: <0.001 <0.001 <0.001 <0.001
Mild(339)24.120.114.9 19.716.3 16.9 17.4 24.320.7
Moderate (803)57.028.116.3 27.517.6 24.4 20.6 33.122.1
Severe(266)18.932.720.2 32.423.1 26.8 22.7 39.624.2
Gender: <0.001 <0.001 <0.001 <0.001
Women(1009)71.728.717.3 28.318.9 24.420.9 34.023.0
Men(399)28.322.916.7 22.218.6 19.719.4 27.721.6
Age groups: 0.321 0.769 0.380 0.046
18–20(697)49.526.616.9 26.418.5 22.620.4 31.022.4
21+(711)50.527.517.7 26.719.4 23.6 20.8 33.423.0
Work: 0.047 0.028 0.178 0.329
No(964)68.526.416.8 25.818.1 22.620.0 31.822.5
Yes(444)31.528.418.4 28.320.6 24.2 21.8 33.123.2
Residency: 0.526 0.731 0.324 0.532
With parents(1045)74.226.916.8 26.518.6 22.719.8 32.022.2
Alone(363)25.827.618.8 26.920.1 24.1 22.8 32.924.2
Depression: <0.001 <0.001 <0.001 <0.001
Normal(559)39.719.614.2 20.216.1 16.617.2 21.118.4
Moderate (443)31.527.515.6 27.218.3 23.219.2 32.819.9
Severe(406)28.836.918.0 34.820.1 32.0 23.1 46.822.7
Stress: <0.001 <0.001 <0.001 <0.001
Normal (911)64.721.213.9 21.515.7 18.1 17.8 23.718.3
Moderate (259)18.433.315.5 32.118.9 28.220.5 41.319.2
Severe(238)16.942.619.1 40.121.9 36.5 23.4 54.922.2
* One-way analysis of variance test for linear trends (nomophobia, depression, stress) and t test for independent samples (gender, age groups, work, residency).
Table 2. Total effect models. Multiple regression-derived coefficients for perceived health scales with nomophobia 100-point scale as the explanatory variable *.
Table 2. Total effect models. Multiple regression-derived coefficients for perceived health scales with nomophobia 100-point scale as the explanatory variable *.
Health Scalesb **95% CIp Value
Total Health0.220.17–0.26<0.001
Musculoskeletal0.220.17–0.27<0.001
Hearing and Vision0.170.12–0.23<0.001
Psychosomatic0.260.20–0.32<0.001
* Adjusted for gender, age categories, working status, residency, and the total time of smartphone usage. ** Total effect on health scales.
Table 3. Mediation analysis with perceived health scales as outcome variables.
Table 3. Mediation analysis with perceived health scales as outcome variables.
  Total Healthb1 *95% CIp ValueMediating Variables b2 **95% CI
Nomophobia0.10(0.06, 0.14)<0.001Depression0.03(0.01, 0.04)
Gender (women vs. men)3.61(1.93, 5.29)<0.001Stress0.09(0.07, 0.12)
Age groups (18–20 vs. 21+)−0.61(−2.19, 0.98)0.451Total indirect effect0.12(0.09, 0.15)
Work (yes vs. no)3.22(1.54, 4.90)<0.001
Residency
(with parents vs. alone)
−0.62(−2.36, 1.13)0.488
Total time of smartphone usage 0.01(−0.02, 0.03)0.565
  Musculoskeletalb1 *95% CIp ValueMediating Variablesb2 **95% CI
Nomophobia0.12(0.07, 0.17)<0.001Depression0.02(0.01, 0.03)
Gender (women vs. men)4.00(2.01, 5.99)<0.001Stress0.08(0.06, 0.11)
Age groups (18–20 vs. 21+)0.21(−1.66, 2.07)0.829Total indirect effect0.10(0.08, 0.13)
Work (yes vs. no)3.93(1.95, 5.91)<0.001
Residency
(with parents vs. alone)
−0.41(−2.46, 1.65)0.700
Total time of smartphone usage0.01(−0.02, 0.04)0.646
  Hearing and Visionb1 *95% CIp ValueMediating Variablesb2 **95% CI
Nomophobia0.07(0.01, 0.12)0.014Depression0.02(0.01, 0.04)
Gender (women vs. men)3.00(0.79, 5.23)0.008Stress0.08(0.05, 0.11)
Age groups (18–20 vs. 21+)−0.74(−2.83, 1.34)0.484Total indirect effect0.10(0.08, 0.13)
Work (yes vs. no)2.50(0.29, 4.72)0.027
Residency
(with parents vs. alone)
−1.25(−3.54, 1.05)0.287
Total time of smartphone usage−0.01(−0.04, 0.03)0.832
  Psychosomaticb1 *95% CIp ValueMediating Variablesb2 **95% CI
Nomophobia0.08(0.02, 0.13)0.004Depression0.04(0.02, 0.06)
Gender (women vs. men)3.23(1.12, 5.35)0.003Stress0.14(0.11, 0.18)
Age groups (18–20 vs. 21+)−2.51(−4.50, −0.52)0.014Total indirect effect0.18(0.14, 0.22)
Work (yes vs. no)2.14(0.03, 4.25)0.047
Residency
(with parents vs. alone)
−0.52(−2.71, 1.67)0.643
Total time of smartphone usage0.20(−0.01, 0.05)0.229
* Direct effect of nomophobia on health scales. ** Indirect effect of depression and stress on health scales.
Table 4. Perceived health 100-point scales regarding smartphone usage and social media involvement.
Table 4. Perceived health 100-point scales regarding smartphone usage and social media involvement.
Total Health Musculoskeletal Hearing/Vision Psychosomatic
N%MeanStd. Dev.p Value *MeanStd. Dev.p Value *MeanStd. Dev.p Value *MeanStd. Dev.p Value *
Checking 0.002 0.046 0.018 <0.001
Up to 10 min(508)36.128.817.6 27.919.8 24.921.6 34.922.8
20 min(264)18.827.016.2 26.317.4 22.420.1 33.521.6
>20 min(636)45.225.717.5 25.618.9 21.920.0 29.522.9
Years of phone ownership 0.638 0.692 0.109 0.279
≤5 years(278)19.726.317.2 25.718.2 23.020.7 30.923.1
6–7 years(528)37.527.517.3 27.119.0 23.520.8 32.622.5
8–9 years(306)21.726.617.5 26.119.5 22.820.5 31.722.4
10+ years(219)15.627.617.2 27.018.9 22.720.3 33.823.4
Phone usage, hours/day <0.001 <0.001 0.031 <0.001
≤5 h/day(611)43.425.116.5 24.217.2 22.120.8 30.022.7
6–9 h/day+ (491)34.927.717.7 27.820.1 22.919.8 32.222.6
10+ h/day(306)21.730.017.9 29.220.0 25.421.5 36.522.5
Calls/day 0.204 0.194 0.984 0.103
≤5(767)54.526.717.3 26.218.8 23.320.7 31.422.5
6–9(364)25.926.616.2 25.918.0 22.420.1 32.521.9
10+(277)19.728.518.7 28.320.7 23.621.1 34.024.3
Messages/day 0.618 0.683 0.398 0.927
≤10(443)31.527.416.4 26.817.9 23.720.2 32.622.3
11–29(381)27.127.018.5 26.720.0 23.220.8 31.524.1
30+(584)41.526.817.2 26.319.1 22.620.9 32.422.2
Friends 0.431 0.214 0.469 0.445
≤200(354)25.126.416.8 25.617.8 23.721.5 31.122.8
201–499(202)14.326.317.6 25.819.2 22.220.5 31.723.7
500–999(304)21.628.217.1 27.219.0 24.521.2 34.122.6
1000+(548)38.927.117.6 27,019.6 22.319.8 32.122.4
Followers on social media 0.218 0.138 0.881 0.208
≤200(378)26.826.316.8 25.618.7 22.920.5 31.321.6
201–499(382)27.126.816.7 26.018.0 23.720.9 31.623.3
500–999(410)29.127.617.7 27.519.4 22.620.4 33.022.5
1000+(238)16.927.718.4 27.320.2 23.120.8 33.223.9
* One-way analysis of variance test for linear trends.
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Notara, V.; Vagka, E.; Lagiou, A.; Gnardellis, C. Perceived Health and Nomophobia among Young Adults: The Mediating Role of Depression and Stress. Sustainability 2024, 16, 96. https://doi.org/10.3390/su16010096

AMA Style

Notara V, Vagka E, Lagiou A, Gnardellis C. Perceived Health and Nomophobia among Young Adults: The Mediating Role of Depression and Stress. Sustainability. 2024; 16(1):96. https://doi.org/10.3390/su16010096

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Notara, Venetia, Elissavet Vagka, Areti Lagiou, and Charalambos Gnardellis. 2024. "Perceived Health and Nomophobia among Young Adults: The Mediating Role of Depression and Stress" Sustainability 16, no. 1: 96. https://doi.org/10.3390/su16010096

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