Aydın, Alay, Yılmaz, and Can: The Interplay Between Problematic Internet Use, Anxiety, Depression and Functional Impairment in Front-Line Healthcare Workers During the COVID-19 Pandemic

Abstract

Objective

We aimed to assess the interplay between functional impairment and anxiety, depression, and problematic Internet use levels in front-line healthcare workers who work in inpatient clinics of coronavirus disease-2019 (COVID-19) during the COVID-19 pandemic.

Methods

Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Internet Addiction Test (IAT), and Sheehan Disability Scale (SDS) were administered to assess the depression, anxiety, problematic Internet use, and functional impairment levels of the participants.

Results

Two hundred thirteen participants were enrolled in the present study. Medical doctors showed significantly higher scores of IAT than the nurses and other medical staff (Kruskal–Wallis=6.519, p=0.038). Levels of SDS total are significantly correlated with scores of IAT (r=0.257, p<0.001), BDI (r=0.383, p<0.001), and BAI (r=0.308, p<0.001). All subdomain scores of SDS (social, family, work) and total scores of SDS were significantly and positively correlated with BAI, BDI, and IAT scores (p<0.05). In the separation mediation analysis, problematic Internet use partially mediated the relationship between anxiety-depression and global functional impairment.

Conclusion

Health politicians should produce policies to develop strategies for coping with consequences of anxiety and depression in healthcare professionals during any health crisis. In addition, we should raise healthcare professionals’ awareness that problematic Internet use is not suitable for dealing with anxiety and depression and may even lead to increase of functional loss.

INTRODUCTION

Coronavirus disease-2019 (COVID-19) is an infectious disease induced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1]. Following the declaration of the novel COVID-19 as a pandemic by the World Health Organization (WHO) on March 11, 2020 [2] people’s manner of living have detrimentally impacted. COVID-19 outbreak has brought about a rise in degrees of psychological distress. As stated by the results of the community-based studies, prevalence of depression is seven times and prevalence of anxiety is three times higher than the global estimated prevalences of depression and anxiety, respectively, before the outbreak prevalences anxiety and depression [3,4].
The Internet gave rise to a huge convenience for the accessibility of information and supplies chances for amusement and social connections. Apart from its advantages excessive usage of the Internet is related with Internet addiction, also named as “problematic Internet use” or “pathological Internet use”. 5 Problematic Internet use is considered a behavioral addiction. In this situation, a person experiences impairments regarding Internet usage management. This uncontrollable Internet usage leads to failures and indifferences to other areas of interest in daily life. Although a person experiences adverse outcomes, Internet usage does not end [6,7]. In a recent meta-analysis with 2,123,762 participants from 64 countries, problematic Internet use prevalence was found as 14.22% [8]. Additionally, during the COVID-19 outbreak an increment of problematic Internet use was found in the general population [5].
Functioning is defined as the capability of an individual to accomplish his/her roles well enough in daily life [9]. Functioning is composed of many different fields including the ability to work, to perform daily activities single and mental operations, organize financial issues, experience friendships, and get pleasure from leisure activities [10]. Problematic Internet use may lead to alcohol abuse, attention-deficit hyperactivity disorder, depression, and anxiety [11,12] and additionally problematic Internet use may lead to functional impairment [12,13].
Health care professionals are adversely influenced amongst the outbreak period [14]. In a meta-analysis with participants considering healthcare workers, during the COVID-19 pandemic, prevalence of anxiety was found as 24.94% and prevalence of depression was found as 24.83% [15]. High working hours, safety measures, attenuated social interactions may have led to the increment of anxiety and depression levels in healthcare workers [16]. This huge anxiety and depression effect gave rise to adverse consequences on mental health of healthcare workers. While researching the effects of the COVID-19 pandemic on front-line healthcare workers, differences were found between front-line and second-line healthcare workers. It was reported that front-line healthcare workers showed higher anxiety and depression levels than second-line healthcare workers during the pandemic [17,18]. This result indicates that we should consider the effects of the pandemic more on front-line health workers. During the COVID-19 pandemic, problematic Internet use was related to high depression and anxiety levels, poor sleep quality, and decreased sense of well-being in participants with resident doctors and medical students [19]. However, the effects of problematic Internet use on front-line healthcare workers have yet to be investigated. There is a gap in the literature. Before that, any study has not investigated the relationship between problematic Internet use, anxiety, depression, and functional impairment of front-line healthcare workers who work in inpatient services during the COVID-19 pandemic.
The main aim of the study was to investigate the association between problematic Internet use and functional impairment of the front-line healthcare workers who work in the COVID-19 inpatient clinics. As a secondary aim, we assessed the association between problematic Internet use and anxiety and depression levels. We proposed a main hypothesis that anxiety, depression, and problematic Internet use levels would be positively associated with functional impairment levels of front-line healthcare workers. Additionally, the association between functional impairment levels and levels of anxiety and depression would be mediated by problematic Internet use levels.

METHODS

Study design and participants

The study was performed in inpatient COVID-19 clinics of Atatürk University Hospital between June 2020 and January 2021. The front-line healthcare workers in this study mentions to the medical and health staff who works in the COVID-19 inpatient sevices. All the participants were administered tests to assess anxiety, depression, problematic Internet use, functional impairment levels, and sociodemographic features via the online survey. A sociodemographic and clinical form that was developed for this study by the researchers was used in the present study. The Turkish versions of the Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), Internet Addiction Test (IAT) were administered for the sake of to assess anxiety, depression, and problematic Internet use levels. Functional impairment was assessed with Sheehan Disability Scale (SDS). Participants ticked a box to give an informed consent at the beginning of the survey. At the end of the survey, the whole sample was consisted of 213 participants. The ethics committee of the Atatürk University Faculty of Medicine approved this study (date: 28/05/2020, meeting number: 06, decision no: 41).

Measures

BAI

BAI is a Likert type scale and consists of 21 items. The total score ranging from 0 to 63. Higher scores are positively related with higher anxiety levels [20]. It was shown to be valid and reliable in a Turkish population [21]. We found robust internal consistency of the BAI in this study (Cronbach’s α=0.95).

BDI

BDI is a Likert type scale and consists of 21 items. The total score ranging from 0 to 63. Higher scores are positively related with higher depression levels [22]. This scale was shown to be valid and reliable in a Turkish population [23]. In our study, we found excellent internal consistency for this scale (Cronbach’s α=0.93).

IAT

The IAT is a self-report questionnaire and consists of 20 items rated on a six-point, ranging from 0 (does not apply) to 5 (always applies). The total score ranging from 0 to 100. Higher scores are positively related with increased Internet usage [24]. This scale was shown to be valid and reliable in a Turkish population and a cutoff value of 50 or higher has been proposed as indicative of problematic Internet use [25]. We found excellent internal consistency for this scale in this study (Cronbach’s α=0.93).

SDS

Functional impairment was measured by the SDS. SDS investigates the functional loss experienced by a person considering family life/home (SDS family), social life/leisure activities (SDS social), and work/school (SDS work) on a scale from 0 to 10. SDS is a self report scale and consists of 3 items related with above-mentioned domains. The total SDS score (SDS total) represents the global functional impairment and it is the sum of the 3 items, and high scores refer to high levels of functional impairment [26]. We found Cronbach’s α as 0.78 for this scale in the present study.

Statistical analyses

Statistical package for the social sciences (SPSS v22; IBM Corp., Armonk, NY, USA) program was used to analyze the research data. Categorical variables were presented as numbers and percentages, and numerical variables as mean±standard deviation and median (1st quartile–3rd quartile). In order to investigate the suitability of the numerical variables to the normal distribution Kolmorov–Smirnov Test, z values calculated for skewness and kurtosis, and graphing methods were used. Mann–Whitney U tests were used for comparisons of non-normally distributed numerical variables between two independent groups, and Kruskal–Wallis tests were used for variance analysis. Spearman rho correlation analysis was used to investigate the relationships between independent variables and scale scores. We used the statistical package for the social sciences PROCESS macro for mediation analyses [27]. Analyses were tested for indirect effects using 5,000 bootstrapped samples and 95% confidence interval (CI) [28] as well as following recommended steps for mediation analyses. The hypothesized model examined whether problematic Internet use mediated the relationship between depression (BDI scores) or anxiety (BAI scores) and global functional impairment (SDS total scores). Pathways were considered statistically significant if the 95% CI did not include zero. Statistical significance level was accepted as p<0.05 in all analyses.

RESULTS

Sample features

The sociodemographic characteristics of the participants are presented in Table 1. Our sample comprised of 213 front-line healthcare workers (mean age 30.7±7.2 years and 71.4% of the participants were females). 56.8% of the participants were nurses, 33.3% of them were medical doctors and 9.9% of them was the other clinic staff.
Descriptive statistics of the clinical scales are presented in Table 2. Medians of the IAT, BDI, BAI and SDS total were 18.0 (10.0–28.0), 11.0 (5.0–17.0), 7.0 (2.0–18.0), 8.0 (5.0–13.0), respectively. Comparison of sociodemographic and clinical features in terms of anxiety, depression, problematic Internet use and functional impairment of the participants are shown in Table 3. Female participants had significantly higher BAI scores than males (Mann–Whitney U test [U]=3641.5, p=0.014). Single participants had higher IAT scores (U=3426.5, p<0.001), BDI scores (U=4552.5, p=0.018), BAI scores (U=4685.5, p= 0.039) than maried ones. Participants who are living alone had significantly higher IAT scores than participants who are not living alone (Kruskal–Wallis [KW]=9.719, p=0.020). Medical doctors’ IAT scores were significantly higher than the nurses and other medical staff (KW=6.519, p=0.038). Front-line medical workers who had chronic medical disorder had significantly higher BAI scores than the participants without any chronic medical disorder (U=1406.5, p=0.045). Participants who have a psychiatric disorder history had significantly higher IAT scores (U=1592.5, p=0.017), BDI scores (U= 1288.5, p=0.001), BAI scores (U=1133.5, p< 0.001) than the participants without any history of psychiatric disorder.

Correlation analyses

The results of the Spearman’s correlation analysis of the anxiety, depression, problematic Internet use and functional impairment scores are presented in Table 4. The analysis revealed that scores of total SDS are positively and significantly correlated with scores of IAT (r=0.257, p<0.001), BDI (r=0.383, p<0.001) and BAI (r=0.308, p<0.001). Additionally, SDS work/school subdomain scores are significantly and positively correlated with scores of IAT (r=0.207, p=0.002), BDI (r=0.195, p=0.004), BAI (r=0.165, p=0.016). SDS social life subdomain scores are significantly and positively correlated with problematic Internet use (r=0.233, p=0.001), BDI (r=0.361, p<0.001) and BAI (r=0.279, p<0.001). SDS family subdomain scores are positively and significantly correlated with scores of IAT (r=0.250, p<0.001), BDI (r=0.361, p<0.001), and BAI (r=0.310, p<0.001). In terms of relationship between problematic Internet use and anxiety and depression levels of participants, scores of IAT were significantly and positively correlated with scores of BDI (r=0.317, p<0.001), and BAI (r=0.249, p<0.001). Scatter plots of the correlation analysis for SDS family, SDS social, SDS work, SDS total, IAT, BDI, and BAI are presented in Figure 1.

Mediation analyses

We observed a significant association between depression and functional impairment (c path or total effect=0.26, standard error [SE]=0.03, p<0.001, 95% CI=0.18–0.33). Further, we observed a positive association between depression and problematic Internet use (a-path, higher depression scores associated with excessive problematic Internet use), as well as between problematic Internet use and functional impairment (b-path, with excessive Internet use associated with more functional impairment) (Figure 2). The indirect effect (ab) of problematic Internet use on functional impairment was also significant; the direct effect including the mediator was reduced but still significant (c’=0.23, SE=0.03, p<0.001, 95% CI=0.16–0.31), indicating that the relationship between depression and functional impairment was partially mediated by problematic Internet use.
We observed a significant association between anxiety and functional impairment (c path or total effect=0.20, SE=0.03, p<0.001, 95% CI=0.13–0.26). Further, we observed a positive association between anxiety and problematic Internet use (a path, higher anxiety scores associated with excessive problematic Internet use), as well as between problematic Internet use and functional impairment (b-path, with excessive Internet use associated with more functional impairment) (Figure 3). The indirect effect (ab) of problematic Internet use on functional impairment was also significant; the direct effect including the mediator was reduced but still significant (c’=0.17, SE=0.03, p<0.001, 95% CI=0.11–0.24), indicating that the relationship between anxiety and functional impairment was partially mediated by problematic Internet use. Regarding the mediation analysis, we wish to mention the difference between direct and indirect effects. Direct effects, as the name implies, deal with the direct impact of one individual on another when not mediated or transmitted through a third individual. Indirect effects can be defined as the impact of one organism or species on another, mediated or transmitted by a third.

DISCUSSION

In the present study, we found that front-line healthcare workers’ problematic Internet use levels partially mediated the association between functional impairment and anxiety-depression levels of them. Additionally, consistent with one of the our main hypotheses, problematic Internet use was significantly positively correlated with overall and all domains of functional impairment scores (family life/home, social life/leisure activities, and work/school). Furthermore, in the present study, anxiety, and depression levels of front-line health care workers were significantly positively correlated with problematic Internet use, overall functional impairment, and all domains of functional impairment (family life/home, social life/leisure activities, and work/school).
The well-being of healthcare workers is becoming more and more important day by day. The research that investigates healthcare workers’ mental health does not reveal encouraging results. Healthcare workers experience elevated rates of depression, anxiety, burnout, and stress [29,30]. Additionally, these mental health problems of healthcare workers may give rise to medical errors and functional impairment [31]. A study conducted with 1,800 nurses reported that over half of the study participants showed suboptimal mental health. Depression was the first reason for the medical errors in this study sample [32]. Suicide is a common problem among healthcare workers, and it was reported that the risk of suicide was increased in nurses, physicians, and dentists compared to the general population [33]. The results mentioned above are from before the COVID-19 pandemic. After the pandemic, healthcare workers faced additional stressors, working loads, and mental health problems. Besides this, online education, socialization, and trade have increased even more after the pandemic and have become widely used in daily life in the post-pandemic world. Thus, the effects of Internet usage on mental health became even more critical.
In a meta-analysis of data from 31 nations, problematic Internet use prevalence was associated with inversely with quality of life [34]. Problematic Internet use was related to impoverished health-related quality of life, experiencing hardships in everyday activities [35], and impairments in neurocognitive functions [36]. Previously, problematic Internet use was associated with depression and anxiety in university students [37]. The above results considering the consequences of problematic Internet use were obtained before the COVID-19 pandemic.
In an umbrella review of 44 meta-analyses, during the COVID-19 pandemic, 29.9% of hospital workers reported anxiety symptomatology and 28.4% of them reported depression symptomatology, and about 40%, reported sleep disorder symptomatology [38]. Additionally, front-line healthcare workers were impacted more adversely than second-line healthcare workers during this time frame. It was reported that front-line healthcare workers showed higher anxiety, depression, burnout, and possibly post-traumatic stress disorder than second-line healthcare workers during the pandemic [17,18,39].
During the COVID-19 outbreak, an increment of problematic Internet use was found in the general population [5]. During this period, problematic Internet use was associated with high depression and anxiety levels, impaired sleep quality, and decreased sense of well-being in participants with resident doctors and medical students [19]. When we deemed the high anxiety and depression levels of front-line healthcare workers and the increment of Internet use during the COVID-19 outbreak, front-line healthcare workers may use the Internet as a maladaptive way to manage with these factors during the COVID-19 pandemic. Confinement to homes and social restrictions in daily life activities may have led the front-line healthcare workers to increase problematic Internet use [40]. The previously mentioned results regarding consequences of problematic Internet use [34-37] may be explanatory for the present study’s result of the mediating effect of problematic Internet use on the association of anxiety and depression and functional impairment of participants in the present study. The current study’s result pertaining to the mediating effect of problematic Internet use on anxiety and depression’s association with overall functional impairment of the front-line healthcare workers may deserve further attention. Based upon our results, in this group of healthcare workers, as well as anxiety and depression levels, problematic Internet use levels should be rigorously assessed to alleviate the front-line healthcare workers’ psychosocial functioning problems amid the pandemic.
Before the pandemic, medical doctors and nurses had levels of anxiety, depression, and suicide ideations higher than the general population. Additionally, death by suicide was more common in medical doctors than in other occcupations [41,42]. Additionally, even before the pandemic, problematic Internet use’s positive association with depression, burnout, and perceived stress was reported in a sample consisting of resident doctors [43]. Considering the increase in anxiety and depression after the pandemic, the findings of the present study should be taken into consideration. The mediating effect of problematic Internet use may play adverse roles on the other associated factors with depression and anxiety in healthcare workers.
In the current study, the problematic Internet use of medical doctors was higher than the nurses and the other clinical staff. In a meta-analysis, problematic Internet use prevalence of medical students was found as five times higher than the general population [44]. In a study performed in a tertiary hospital with participants of resident doctors, increased depression, burnout, and perceived stress was related with problematic Internet use [43]. Considering the high levels of problematic Internet use in medical doctors in the present study and adverse consequences of problematic Internet use in resident doctors in the aforementioned study, the future studies may give priority to establish interventions to reduce the adverse consequences of problematic Internet use in medical doctors.
The present study has some crucial limitations. In the present study, a narrower timeframe would be better. Risk perception may have changed over time throughout our study period (6 months), affecting our results. The cross-sectional design of the study limits to infer causality from our results. In line with the present study’s results, during the pandemic, problematic Internet use may affect the functional impairment of front-line healthcare workers via the mediating effect of anxiety and depression. On the other hand, there is a probability that functional impairment may affect problematic Internet use via the mediating effect of depression and anxiety. In a recent study, researchers found that in the COVID-19 pandemic, depression symptoms significantly mediated the association between behavioral inhibition-behavioral activation systems and problematic Internet use. This study evaluated problematic Internet use using the same instrument as the present study (IAT). However, the participants were composed of adolescents [45]. In another study, during the COVID-19 pandemic, anxiety mediated problematic Internet use’s effect on adolescent participants’ aggressive behavior. In this study, a different problematic Internet use assessment tool was used [46]. Follow-up studies could be performed in future pandemics to unveil the causal associations between problematic Internet use, anxiety, depression, and functional impairment during the pandemic. Another area for improvement of the present study is its online assessment method. The online assessment method of the present study may have caused difficulties in reaching healthcare workers who are not fans of the Internet. The reaching difficulty may have yielded a selection bias. The selection bias may have affected the present study’s sample size. Additionally, among people, there are inequalities regarding access to digital-based technologies. This inequality is called the digital divide [47]. The digital divide may have also elicited an influence on the number of participants the present study has reached. On the other hand, in the pandemic time frame, people were unwilling to have face-to-face contact, and online data collection was necessary. Consequently, the reaching difficulties may have affected the present study’s results. Another limitation of the present study is that it does not capture the working experiences of the study participants. Being a young age healthcare worker may resemble less working experience. Furthermore, being a younger healthcare worker was related to adversely affected mental health during the COVID-19 pandemic [39]. Future studies may evaluate the effects of the working experiences of front-line healthcare workers on functional impairment. The self-report type of data collection in the present study should be considered, too. We evaluated problematic Internet use, anxiety, depression, and functional impairment with frequently used self-report instruments. However, future studies may use different ways of data collection, such as clinical interviews or observational methods, to assess these variables. Therefore, the results of our study should be interpreted with caution.
The present study emphasizes the interplay between functional impairment and problematic Internet use, anxiety, and depression in front-line healthcare workers. Our findings introduce that front-line healthcare workers’ functional impairment are positively associated with their problematic Internet use, anxiety, and depression levels during the COVID-19 pandemic. Additionally, the association between levels of anxiety-depression and functional impairment of front-line health care workers was partially mediated by their problematic Internet use levels. These results may suggest considerable interventions for the sake of improving psychosocial functioning in front-line healthcare workers. For these results to impact the daily working life of front-line healthcare workers, it is essential to inform healthcare professionals. Awareness of the adverse effects of problematic Internet use may raise awareness of this issue in this population. Considering possible future pandemics, front-line healthcare workers need to be trained on the adverse effects of excessive Internet use before pandemics. Authorities may inform healthcare workers regarding the adverse effects of excessive Internet use. Thus, healthcare professionals use more helpful methods to cope with intense stress during pandemic periods. In addition to amusement aims, Internet use is now accepted as an ordinary activity to perform daily necessities worldwide in many areas of daily life. So, Internet use is growing globally. The results of the present study regarding the mediating effects of problematic Internet use may be an option for worldwide healthcare systems to create policies to overcome the psychosocial difficulties of front-line healthcare workers. Subsequent studies may focus on other factors that may have effects on psychosocial functioning of front-line health care workers with larger samples.

Notes

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: all authors. Data curation: Esat Fahri Aydın, Handan Alay, Fatma Kesmez Can. Formal analysis: Sinan Yılmaz. Investigation: Esat Fahri Aydın. Methodology: all authors. Resources: Esat Fahri Aydın, Handan Alay. Writing—original draft: Esat Fahri Aydın, Sinan Yılmaz. Writing—review & editing: all authors.

Funding Statement

None

ACKNOWLEDGEMENTS

The authors thank to all the participants of the present study.

Figure 1.
Scatter plots of the correlation analysis for SDS family, SDS social, SDS work, SDS total, IAT, BDI, and BAI. SDS family, Sheehan Disability Scale family life/home; SDS social, Sheehan Disability Scale social life/leisure activities; SDS work, Sheehan Disability Scale work/school; ITA, Internet Addiction Test; BDI, Beck Depression Inventory, BAI, Beck Anxiety Inventory; SDS, Sheehan Disability Scale.
pi-2023-0022f1.tif
Figure 2.
The partial mediation role of problematic Internet use in the relationship between depression levels and disability. ***p<0.001. BDI, Beck Depression Inventory; IAT, Internet Addiction Test; SDS, Sheehan Disability Scale.
pi-2023-0022f2.tif
Figure 3.
The partial mediation role of problematic Internet use in the relationship between anxiety levels and functional impairment. ***p<0.001. BAI, Beck Anxiety Inventory; IAT, Internet Addiction Test; SDS, Sheehan Disability Scale.
pi-2023-0022f3.tif
Table 1.
Sociodemographic and clinical features of the participants (N=213)
Variables Value
Age (yr) 30.7±7.2
Sex
 Male 61 (28.6)
 Female 152 (71.4)
Marital status
 Married 95 (44.6)
 Single 118 (55.4)
Living with whom
 Family 129 (60.6)
 Friends 15 (7.0)
 Himself/herself 69 (32.4)
Profession
 Other medical staff* 21 (9.9)
 Medical doctor 71 (33.3)
 Nurse 121 (56.8)
Chronic medical disorder
 Yes 20 (9.4)
 No 193 (90.6)
Psychiatric disorder history
 Yes 24 (11.3)
 No 189 (88.7)

Values are presented as number (%) or mean±standard deviation.

* midwives and patient care technicians

Table 2.
Descriptive statistics of clinical scales
Variables Median (Q1–Q3)
IAT 18.0 (10.0–28.0)
BDI 11.0 (5.0–17.0)
BAI 7.0 (2.0–18.0)
SDS family 3.0 (1.0–6.0)
SDS social 4.0 (1.0–7.0)
SDS work 1.0 (0.0–2.0)
SDS total 8.0 (5.0–13.0)

IAT, Internet Addiction Test; BDI, Beck Depression Inventory; BAI, Beck Anxiety Inventory; SDS family, Sheehan Disability Scale family life/home; SDS social, Sheehan Disability Scale social life/leisure activities; SDS work, Sheehan Disability Scale work/school; SDS, Sheehan Disability Scale

Table 3.
Distrubution of clinical scales according to sociodemographic and clinical variables
Variables IAT
BDI
BAI
SDS total
Mean±SD Median (Q1–Q3) Statistics Mean±SD Median (Q1–Q3) Statistics Mean±SD Median (Q1–Q3) Statistics Mean±SD Median (Q1–Q3) Statistics
Sex U=5304.5, p=0.100 U=4257.0, p=0.351 U=3641.5, p=0.014 U=4715.0, p=0.844
 Male 23.2±17.1 19.0 (11.0–34.0) 11.8±10.2 110 (4.0–16.0) 8.4±10.7 3.0 (1.0–13.0) 9.4±7.1 8.0 (5.0–13.0)
 Female 18.2±11.3 16.0 (9.0–26.0) 13.2±10.7 11.0 (5.0–17.0) 11.9±12.3 7.5 (2.5–19.5) 8.9±6.1 8.0 (4.5–12.5)
Marital status U=3426.5, p<0.001 U=4552.5, p=0.018 U=4685.5, p=0.039 U=5402.5, p=0.646
 Married 15.3±12.6 12.0 (5.0–21.0) 11.3±10.2 8.0 (4.0–17.0) 9.1±10.5 5.0 (1.0–14.0) 8.8±6.1 8.0 (5.0–11.0)
 Single 23.1±13.0 22.5 (14.0–30.0) 13.9±10.7 12.0 (7.0–16.0) 12.3±12.9 8.0 (2.0–18.0) 9.3±6.6 8.0 (4.0–14.0)
Living with whom KW=9.719, p=0.020 KW=0.608, p=0.750 KW=3.099, p=0.302 KW=3.611, p=0.534
 Family 17.8±12.7 16.0 (8.0–25.0)* 12.8±11.5 10.0 (4.0–18.0) 10.5±12.2 6.0 (1.0–18.0) 9.3±6.2 8.0 (6.0–13.0)
 Friends 20.2±14.7 16.0 (8.0–34.0) 13.5±10.3 11.0 (7.0–14.0) 8.7±10.6 6.0 (1.0–13.0) 8.1±7.6 8.0 (2.0–18.0)
 Herself/himself 23.0±13.9 24.0 (14 .0–29.0)* 12.5±8.8 12.0 (7.0–16.0) 21.1±11.7 9.0 (3.0–19.0) 8.8±6.5 8.0 (3.0–12.0)
Occupation KW=6.519, p=0.038 KW=0.039, p=0.981 KW=2.431, p=0.296 KW=0.089, p=0.957
 Other medical staff 14.6±11.3 15.0 (6.0–19.0)* 13.1±11.0 10.0 (4.0–24.0) 14.1±12.0 20.0 (1.0–23.0) 8.8±4.4 8.0 (8.0–9.0)
 Medical doctor 22.6±14.7 21.0 (11.0–29.0)* 12.3±9.2 11.0 (5.0–16.0) 8.6±9.8 6.0 (2.0–13.0) 9.5±7.5 8.0 (3.0–17.0)
 Nurse 18.8±12.6 16.0 (9.0–28.0) 13.0±11.2 11.0 (5.0–17.0) 11.7±12.9 8.0 (1.0–18.0) 8.8±6.0 8.0 (6.0–12.0)
Chronic medical disorder U=2179.0, p=0.341 U=1795.0, p=0.606 U=1406.5, p=0.045 U=1891.5, p=0.882
 Yes 16.6±10.4 16.5 (9.0–23.0) 13.0±8.6 11.0 (5.5–18.5) 15.1±12.2 11.0 (5.5–24.5) 9.2±5.2 8.0 (6.0–10.0)
 No 19.9±13.7 18.0 (10.0–28.0) 12.8±10.7 11.0 (4.0–17.0) 10.4±11.9 7.0 (2.0–16.0) 9.0±6.5 8.0 (4.0–13.0)
Psychiatric disorder history U=1592.5, p=0.017 U=1288.5, p=0.001 U=1133.5, p<0.001 U=2377.0, p=0.698
 Yes 25.5±13.7 24.5 (15.0–31.5) 20.8±14.2 16.0 (10.5–25.0) 21.8±16.9 18.0 (8.5–24.5) 8.8±7.0. 8.0 (3.0–15.5)
 No 18.9±13.2 16.0 (9.0–26.0) 11.8±9.5 10.0 (4.0–16.0) 9.5±10.4 6.0 (1.0–14.0) 9.1±6.3 8.0 (5.0–12.0)

* significant differences in post-hoc analyses.

midwives and patient care technicians.

IAT, Internet Addiction Test; BDI, Beck Depression Inventory; BAI, Beck Anxiety Inventory; SDS, Sheehan Disability Scale; SD, standard deviation; U, Mann–Whitney U test; KW, Kruskal–Wallis

Table 4.
Spearman correlation analysis between the clinical scales
SDS social SDS work IAT BDI BAI SDS total
SDS family
 r 0.801 0.519 0.250 0.361 0.310 0.928
 p <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
SDS social
 r 0.396 0.233 0.361 0.279 0.922
 p <0.001 0.001 <0.001 <0.001 <0.001
SDS work
 r 0.207 0.195 0.165 0.597
 p 0.002 0.004 0.016 <0.001
IAT
 r 0.317 0.249 0.257
 p <0.001 <0.001 <0.001
BDI
 r 0.666 0.383
 p <0.001 <0.001
BAI
 r 0.308
 p <0.001

SDS social, Sheehan Disability Scale social life/leisure activities; SDS work, Sheehan Disability Scale work/school; IAT, Internet Addiction Test; BDI, Beck Depression Inventory; BAI, Beck Anxiety Inventory; SDS, Sheehan Disability Scale; SDS family, Sheehan Disability Scale family life/home

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