Pattern of smartphone use and its influence on psychosocial features among health professional course scholars: a cross-sectional study

Introduction

Touchscreen technology and a multitude of applications in smartphones have pushed all human cohorts toward constructive and catastrophic traits. Smartphone usage pattern and the risk of developing an addiction varies across age groups, with some age groups exposed to a heightened risk of addiction than others [1]. There is evidence that adolescents and young adults may be at particular risk [2], [3], [4], [5], with a global prevalence rate of 10–67 % [2], 3], and in developing countries such as India itself, the figures range from 24.6 to 44 % [4], [5], [6], [7].

Behavioral addiction defined as “excessive, compulsive, uncontrolled use of one’s phone, leading to a psychological dependence upon the device (or the content on it)” considered a potential disorder and is commonly associated with smartphone usage [8], 9]. Moreover, recent evidence has revealed that excessive smartphone use is associated with many adverse health effects among adolescents with musculoskeletal disorders [10], 11], ophthalmologic disorders [11], 12], sleep difficulties [11], 13], psychopathologies, and psychiatric disorders [11], 14], 15]. In addition to these potentialities, smartphone use may facilitate learning or interfere with educational and professional lives among students [16], which depends entirely on its usage. On the other hand, evidence shows that many university students consider their smartphones a source of entertainment rather than a working instrument [16], 17].

With the benefit of mobile applications, students undergoing medical education prefer most readings through online textbooks (70 %), medical podcasts (60 %), medical calculators (75 %), online lectures (50 %), and note-taking [18]. Regulated usage of smartphones has definitive advantages in educational activities, as evidenced by the design of flexible M-learning modules implemented by various institutions [19]. Nevertheless, many adolescents develop physical and behavioral issues with their usage [18].

With due consideration to the above concerns, there is a need to understand the pattern of smartphone use and its effects on students of health professions. Understanding their technology usage may help prevent them from negatively impacting their health. Therefore, the purpose of this study was to explore the prevalence of smartphone addiction in this specific group of scholars currently pursuing health professional courses and to methodically examine how problematic smartphone usage interferes with their biopsychosocial factors.

The study primarily aimed to a) determine the prevalence of smartphone addiction among medical, dental, and allied health science university scholars and b) to assess how problematic smartphone usage interferes with their physical activity level and health-related quality of life.

Materials and methods

Results

A total of 400 participants were recruited for the study through purposive sampling, of which 125 (31.25 %) were males and 275 (68.75 %) were females. The average age of the participants was 20.8±2.06 years. Among the total population recruited, 136 (34.0 %) were found to be addicted to smartphone usage. Among the categories of students based on their academic programs, the mean value of the smartphone addiction scale was 29.1±10.4, and addiction to smartphones was most prevalent among dentistry students (43 %), followed by medicine (32 %) and allied health science (30.5 %), as depicted in Table 1. Figure 1 illustrates the comparison of smartphone addiction and non-addiction between the medical, dental, and allied health students. Table 2 shows that there were no statistically significant differences in the addiction rates among the students in the three programs. The comparison of smartphone addiction revealed that it was marginally greater in females (34.2 %) than in males (33.6 %); however, these differences were not statistically significant. Figure 2 depicted the Differences in smartphone addiction among gender and course-wise.

Figure 1:

Comparison of smartphone addiction between medical, dental and allied health students.

Table 2:

Gender and course-wise observed values – smartphone usage.

		Smartphone Usage
Gender		Not addicted	Addicted
Male	Observed	83	42
	% within row	66.4 %	33.6 %
Female	Observed	181	94
	% within row	65.8 %	34.2 %
Total	Observed	264	136
	% within row	66.0 %	34.0 %
Course
Medicine	Observed	68	32
	% within row	68.0 %	32.0 %
Dentistry	Observed	57	43
	% within row	57.0 %	43.0 %
AHS	Observed	139	61
	% within row	69.5 %	30.5 %
Total	Observed	264	136
	% within row	66.0 %	34.0 %

1. n, number; %, percentage; AHS, Allied Health Science; p-Value<0.05.

Figure 2:

Difference in smartphone addiction among gender and course-wise.

Table 3 lists the descriptive statistics with the median and mean ± SD values of each domain of the PROMIS-29. When the domains of the PROMIS scale were compared among subjects with and without smartphone addiction, a statistically significant difference was found in all domains between addicted and non-addicted individuals. The scores for physical function were marginally higher in non-smartphone-addicted individuals than in smartphone-addicted individuals (mean difference=0.670, p<0.001). Subjects addicted to smartphones had significantly greater levels of anxiety (mean difference=2.776, p<0.001), depression (mean difference=2.264, p<0.001), and fatigue (mean difference=2.264, p<0.001). The ability to participate in social roles and activities was better among people with no smartphone addiction (mean difference=2.943, p<0.001) than among those who were addicted to smartphones. Pain interference was also found to be greater in people with smartphone addiction (mean difference=1.485, p<0.001) than in non-addicted individuals. The pain intensity was also significantly greater (mean difference=1.014, p<0.001), as depicted in Table 4.

A correlation analysis showed that there was no statistically significant association between Physical activity and any of the domains of PROMIS-29 (Table 5), except sleep disturbance, which showed a weak positive correlation (r=0.144, p<0.05). Physical function domain of PROMIS-29 was found to be significantly different amongst subjects addicted and not addicted to smartphones. A non-significant association was observed between the SAS-SV score and physical activity level. The relationship between smartphone addiction and physical activity is depicted in Figure 3.

Figure 3:

Relationship between smartphone addiction and physical activity.

Discussion

Adolescence is a vital period for physical and intellectual development [26], and in this population, technology-based m-learning encroaches on educational and academic conduct. Moreover, the effect of smartphone use on health varies depending on the basis of the nature and duration of its use. Therefore, the present study explored the prevalence of addiction to smartphone usage among university students in medical, dentistry, and allied health professional courses for whom the use of this technology is necessary for academic purposes. In addition, the study also tried to explore the association between problematic smartphone usage and physical activity levels as well as psychosocial functions of individuals.

The current study revealed that 34 % of the studied population (health professional course students) are addicted to smartphone usage, which is higher than the global prevalence (26.99 %) [27], and the same findings are in line with the range of university students’ problematic smartphone use in countries such as Malaysia (46.9 %) [28], Turkey (39.8 %) [29], China (29.8 %) [30] and Brazil (33.1 %) [31]. Moreover, recent studies where SAS-SV was used to determine the prevalence, addiction rate among adolescent medical students were found to be 39.7 % among Chinese students [32], 21.7 % in Serbia [33], 36 % in Saudi Arabia [34], and 30.2 % in Tunisia [35]. These facts and figures show no such wide variation in the prevalence rate when compared with our study’s addiction prevalence rate, but it’s quite alarming. This highlights that problematic smartphone usage is more of a behavioral addiction, and in the current scenario, smartphone addiction issues are turning more towards a global health concern.

In the present study, which categorized the academic programs of health professional courses, problematic smartphone use was more common among dentistry scholars (43 %), followed by medicine (32 %) and allied health science (30.5 %). Most importantly, higher education institutions have effectively supplemented traditional classroom teaching with emerging social media tools both within and outside the classroom, and more specifically in health professional courses; and their utilization for networking, clinical practice, and educational tasks is more need-based [36], [37], [38]. However, there are no set or standardized guidelines for the timeline or limits on its usage from academic or educational directions. Therefore, the period permissible for its usage as an academic conduit is not specified.

The data collected in our study revealed no significant sex differences in the prevalence of smartphone use. The addiction rate was marginally higher in females (34.2 %) than in males (33.6 %); however, these differences were not statistically significant. This aligns with the results of previous studies conducted in Iran [39], China [40], and Malaysia [41].

It is evident from the present study that the smartphone addiction of the studied population acts as a distraction and creates divergence in their attention from that of the primary tasks. These factors are well reflected in the statistical analysis of the PROMIS scale domains, where it was very clearly shown that students with addiction have greater anxiety, depression, fatigue, and pain interference and intensity. Additionally, a statistically significant difference was found in all the domains of the PROMIS-29 between the subjects with addiction and those without addiction to smartphones. Research has reported similar findings that addiction to smartphones among university students affects their physical and mental health, leading to sleep disorders, reduced academic performance, stress, depression, and weary social relationships [42], [43], [44], [45].

Smartphone addiction may negatively affect physical health by reducing the amount of physical activity [46]. In contrast, in our study, there was no significant statistical association between physical activity levels and domains of PROMIS-29 in the studied population. Except for the sleep disturbance domain (r=0.144, p=0.004), none of the other domains of PROMIS-29 showed any significant relationship with physical activity measured by IPAQ-SF. Similar findings were reported for physical activity and mobile phone addiction among adolescents and young adults aged 18–24 years in another study [47], 48]. Smartphone addiction and participation in physical activity are distinct behaviors, and associating them may be inappropriate without considering other influencing factors. However, studies showed that this behavioral phone addiction has a negative predictive effect on physical activity and a positive impact on social motivation [49]. Additionally, physical activity stimulates the pituitary gland to release endorphins and build up the ability of human dopamine signal transduction to promote positive emotions and replenish self-control [50], 51], which could be the most likely reason behind the lack of a statistical relationship between physical activity level and the Promis-29 domain in our study participants. Furthermore, theoretical frameworks such as the Bio-Psycho-Social model and the Use and Gratifications Theory offer insight into this phenomenon, and the Person-Affect-Cognition-Execution (I-PACE) model signals that smartphone addiction arises from the interplay of individual characteristics, cognitive-emotional processes, and executive function deficits [51].

The present study provides an in-depth view of the characterization of problematic smartphone users among health professional course scholars, for whom the application of smartphones mandates most of their academic activities. Additionally, this study’s analysis provides preparatory evidence for future studies and can be used for public health evaluation and policy-making purposes. Thus, there is an urgent demand for screening for behavioral addiction toward smartphones, evaluating the usage time of smartphones among adolescents and young adults across various academic courses, and most importantly, setting guidelines/recommendations concerning the time limit of their usage for scholarly activities.

However, the present study has several limitations. First, the study participants were exclusively from health professional courses, and the study area was a single center, which may have affected the generalizability of the findings. Incorporating adolescent participants from different and diverse geographical regions could have improved the external validity of the findings. Second, the application of self-reported outcome measures is subject to more subjective perceptions and biases. Third, the study did not address the influence of confounding factors such as the nature of smartphone use, academic performance, socioeconomic state, and other biopsychosocial factors that could impact the relationships observed in this study. Future studies should stress these variables and factors to obtain a clearer picture of the effects of problematic smartphone use on health behavior and quality of life.

Conclusions

The present study revealed a high prevalence of smartphone addiction among health professional adolescent students, with no statistically significant differences in the addiction rates among students in the three programs – medicine, dentistry, and allied health science. Those who are addicted to smartphones show high levels of anxiety, depression, fatigue, and pain interference. However, the current study failed to identify any statistically significant association between smartphone addiction and physical activity. These findings underscore the need for a set recommendation for setting a time limit for the usage of smartphones for both formal and informal academic activities, and to promote awareness of healthy digital habits. Longitudinal studies are required to understand problematic smartphone usage and its detrimental effects based on a biopsychosocial model of disability.