Objectives: Children and adolescents with chronic diseases have more screen exposure time compared with their healthy peers. In this study, we investigated screen exposure time of children who received renal replacement therapy, which included kidney transplant and dialysis treatment, versus a healthy control group.
Materials and Methods: Our study included 55 children and adolescents between the ages of 8 and 18 years. Although 28 participants did not have any chronic disease, 27 had chronic diseases and received renal replacement therapy. Among these patients, 17 had kidney transplant and 10 were receiving dialysis. A sociodemographic information form and the Conners Short-Form Parent Rating Scale were given to parents. Pediatric and adolescent patients completed the Children’s Depression Inventory and Spielberger State-Trait Anxiety Scale-2. We analyzed differences between the groups with and without renal replacement therapy and examined relations between continuous variables.
Results: Duration of television screen time was significantly higher in children and adolescents receiving renal replacement therapy. Patients in the renal replacement therapy group showed a positive correlation between the Conners Short-Form Parent Rating Scale anxiety subscores and duration of smartphone use. In the kidney transplant recipient group, smartphone and computer durations were positively correlated and television duration was negatively correlated with the Conners Short-Form Parent Rating Scale behavioral problems subscores.
Conclusions: Children on renal replacement therapy may be at risk in terms of excessive television exposure. Children who are on dialysis and have had a kidney transplant may be more prone to the negative effects of screen exposure than healthy peers who do not have chronic illnesses. These children and adolescents should be closely monitored to avoid the negative effects of excessive screen exposure.
Key words : Chronic kidney disease, Kidney transplantation, Renal dialysis, Screen time
In the 1970s, children began watching television regularly at the age of 4 years; however, today, they are introduced to digital media at almost 4 months of age.1 It is common knowledge that the duration of screen exposure and related problems in children and adolescents are increasing day by day.2 Although watching television is still the most frequently used screen-based activity for children, computers, tablets, and smartphones have also started to be used in children’s lives from an early age. Among children, these tools are used especially for watching videos and cartoons, playing games, and spending time with friends or meeting new people on social media. Despite common knowledge of screen time limits, many families do not follow these recommendations.3 In the literature, it was emphasized that excessive screen exposure could be associated with sleep problems, obesity, depression, and school failure.4-6 Since television has been in our lives for a long time, its effects are more clear. However, our knowledge about the effects of tablets, smartphones, and touch screens on children’s health and development is limited and needs further understanding.7
Children and adolescents with chronic diseases have been shown to have more screen exposure time than their healthy peers.8 Clark and colleagues reported that children with chronic kidney disease had more screen exposure time than their healthy peers.9 Children who receive renal replacement therapy (RRT) must receive long periods of inpatient treatment; except for those who have had successful kidney transplant operations, this group has to spend hours on hemodialysis or peritoneal dialysis. In addition, hospitalization due to illness may keep these children away from their social environment. Because of the burden of the disease and the treatment process, psychological problems, such as depression and sleep problems, are frequently observed in children who receive RRT.10,11 In addition, children who had kidney transplant were shown to use more presleep screens and had problems in initiating and maintaining sleep.12 With these consideration, it seems that children who are receiving RRT could be at more risk in terms of excessive screen exposure and related problems. As far as we know, information on screen exposure and related problems in children and adolescents who receive RRT is not available in the literature.
In this study, we investigated daily screen exposure time and the reasons for spending time on television, smartphone, tablet, computer, and game console interactions in healthy children and adolescents versus children and adolescents receiving RRT.
Materials and Methods
The study included 39 children and adolescents who were receiving RRT and followed at the Başkent University Ankara Hospital and 28 healthy children and adolescents without any chronic diseases. Among the RRT group, 12 patients had filled the forms incompletely; therefore, there were 27 participants in the RRT group. Age of participants ranged from 8 to 18 years. Inclusion criteria also included the parents’ ability to read, write, and speak Turkish enough to answer the assessment tools.
Sociodemographic information and screen time evaluation form
The evaluation form was an information-gathering tool prepared by researchers to collect sociodemographic and clinical data in accordance with the purpose of the study. In the form, the sociodemographic characteristics of the family and child, the child’s developmental and medical history, family history, diagnosis, method and duration of treatment, and smartphone, computer, tablet, game console, and internet usage times and habits and their purposes for use were collected and examined. Two sociodemographic information forms were prepared for the RRT patients and healthy controls, with questions about the duration of the disease and the treatment received added to the RRT group.
Children’s Depression Inventory
The Children’s Depression Inventory (CDI) was developed by Kovacs13 in 1981 to evaluate depressive symptoms in children. It was adapted into Turkish by Öy14 in 1991. It is a self-reported 3-point Likert scale that includes 27 items; this form was given to children and adolescents to complete. In the scale, the cut-off score was 19, and the highest score was 54. Higher total scores indicate severe depression. According to Öy, test-retest reliability and internal consistency were found to be 0.70 and 80, respectively.
Spielberger Trait Anxiety Scale-2
The Spielberger Trait Anxiety Scale-2 (STAI-2) was developed by Spielberger and colleagues,15 with reliability and validity studies of the scale for Turkish children conducted by Özusta.16 Scores range from 20 to 80 in scale. Higher scores indicate increased anxiety levels. The Cronbach Α coefficient was determined to be 0.81.
Conners Short-Form Parent Rating Scale
The Conners Short-Form Parent Rating Scale (CPRS-48) is a Likert-type scale consisting of 48 questions developed by Goyette and colleagues in 1978.17 It was adapted into Turkish by Dereboy and colleagues in 2007.18 The scale consists of 5 subdimensions: conduct problems, impulsive/hyperactive behavior, learning problems, anxiety, and psychosomatic. Through this scale, the child’s attitudes and behaviors could be evaluated from the parents’ observations. The Cronbach Α coefficient of the scale was 0.90 in the original study.18 For this study, except for the psychosomatic subscales, other subscales were used.
After informed consent was obtained from children and their parents, the sociodemographic information form and the CPRS-48 were given to parents to complete, and the CDI and STAI-2 were completed by children and adolescents. This study was conducted between September 2019 and February 2020.
We used SPSS version 22 software for statistical analyses. Suitability of the variables to normal distribution was examined using the Kolmogorov-Smirnov and Shapiro Wilk tests. Normally distributed variables in descriptive variables are shown as mean values and standard deviations; variables that are not normally distributed are shown as medians. For categorical data, examinations of differences between groups in terms of frequencies were done using chi-square or Fisher tests. When comparing the groups, an independent sample t test was used for continuous and normally distributed variables and the Mann-Whitney U test was used for variables that were not normally distributed. To examine differences between dialysis treatment, kidney transplant, and healthy control groups in terms of continuous variables, the Kruskal Wallis test was performed. For significant values, comparisons in pairs were performed using the Mann-Whitney U test with Bonferroni correction. Correlation coefficients and statistical significance tests for continuous variables were evaluated using the Spearman test because of the variables that did not fit the normal distribution.P< .05 was considered as statistically significant.
Among those who met the inclusion criteria, there were 27 patients in the RRT group (12 girls and 15 boys) and 28 healthy peers without any chronic disease in the control group (18 girls and 10 boys). The groups were similar in terms of male/female participant numbers (P = .14) and age (P = .346). Further details on sociodemographic characteristics of the participants and their families are presented in Table 1 and Table 2.
Results on digital media tools that the children and adolescents or their families owned and their usage areas are shown in Table 3. The results revealed that television viewing time was significantly longer in the group receiving RRT. No statistically significant differences were found between the RRT group versus the control group in terms of exposure to other digital media devices. Duration of screen usage and the related features for the RRT group and the healthy control group are shown in Table 4.
The mean (SD) duration of disease in the RRT group was 8.53 (4.21) years. Among the RRT group, 3 patients (11%) were on peritoneal dialysis, 7 (26%) were on hemodialysis, and 17 (63%) had kidney transplant. The mean (SD) duration of disease for patients who had kidney transplant was 9.2 (3.7) years; duration was 7.3 (4.8) years for patients on dialysis treatment, with no statistically significant difference between these groups (P = .359). No statistically significant differences were shown between the patients who had kidney transplant, patients on dialysis treatment, and healthy controls in terms of screen media usage and CPRS-48 subscale and CDI and STAI-2 scores. Table 5 shows these values among the 3 groups.
When factors regarding duration of screen exposure were examined for patients receiving dialysis treatment, kidney transplant recipients, and healthy control participants, there was a positive correlation between anxiety scores of CPRS-48 and duration of smartphone usage in patients on dialysis (Spearman correlation coefficient of 0.736;P= .024). Also, there was a positive correlation between the behavioral problem subscale and duration of illness (Spearman correlation coefficient of 0.683;P= .043) in patients on dialysis. In this group, there was a negative relationship between CPRS-48 behavioral problem scores and duration of internet usage (Spearman correlation coefficient of -0.686;P= .041).
In the kidney transplant recipient group, duration of illness had a positive correlation with time spent with the family (Spearman correlation coefficient of 0.781;P= .005) and depression scale scores (Spearman correlation coefficient of 0.591;P= .034). Also, in this group, duration of smartphone usage was positively correlated with CPRS-48 anxiety (Spearman correlation coefficient of 0.591;P= .016) and behavioral problem scores (Spearman correlation coefficient of 0.527;P= .036), and television duration was negatively correlated with the CPRS-48 behavioral problems subscale (Spearman correlation coefficient of -0.507;P= .045). In this group, duration of computer usage and the CPRS-48 behavioral problem scores were positively correlated (Spearman correlation coefficient of 0.602;P= .014). We also found that time spent with digital devices by fathers was negatively correlated with digital gaming duration (Spearman correlation coefficient of -0.826;P= .022) but positively correlated with time spent with digital device by mothers (Spearman correlation coefficient of 0.824,P=.023).
In the healthy control group, duration of watching television was negatively correlated with time spent with friends (Spearman correlation coefficient of -0.695;P= .006) and positively correlated with time spent with family (Spearman correlation coefficient of 0.535;P= .012). Time spent by father with digital devices was positively correlated with time spent with tablets by children and time spent by mothers with digital devices (Spearman correlation coefficient of 0.536;P= .012 and Spearman correlation coefficient of 0.510;P= .026, respectively). In contrast, duration of time watching television had a negative correlation with depression scale scores (Spearman correlation coefficient of -0.484,P= .017) and CPRS learning problem subscale scores (Spearman correlation coefficient of -0.396;P= .041). Duration of smartphone use was negatively correlated with CPRS learning problem subscale scores (Spearman correlation coefficient of 0.420;P= .029).
Quality of life in children who receive RRT, such as dialysis and kidney transplant, has been shown to decrease in terms of physical, socio-emotional, and academic fields compared with that shown in healthy children.19 Akber and colleagues found that daily physical activity was lower than recommended in a group of patients between the ages of 7 and 20 years with chronic kidney disease.20 Conditions caused by the disease (eg, anemia and low exercise capacity) and the treatments could make it difficult for these children to exercise.21 These challenges can lead to indoor, sedentary, and screen-based activities in these pediatric patients. Children with chronic kidney disease who are not on dialysis treatment have been shown to have less daily physical activities and more screen time than their healthy peers.9 Consistent with the literature, in our study, we found that daily television watching time of children on RRT was longer than in the healthy children without any chronic disease. Apart from this, no other differences were found between our RRT group and our healthy control group in terms of usage time of other digital devices.
In our healthy control group, we observed that there were more mothers and fathers who spent time with digital devices during the day. Both the effects of socio-economic level and the care burden of having a sick child may have affected this situation. In the control group, the more time that fathers spent with digital devices, the more the time the child spent with tablets. The literature has also reported that parent screen usage times are closely related to their children’s usage time.22 The fact that parents of children in the RRT group used fewer digital devices may have prevented them from the overexposure to digital media.
We observed that duration of smartphone usage increased as anxiety levels increased in both patients undergoing dialysis treatment and those who had kidney transplant. Reinecke suggested that video games can be influential in reducing the negative effects of stress.23 Chen also showed that playing social games on the mobile phone was effective in reducing stress of adolescents, through relaxation and mastery and control experiences.24 Thus, playing digital games on mobile phones may be beneficial in reducing stress, especially for children who stay away from other social resources such as peer support. However, if this situation could not be kept under control, it may pose a risk of game addiction.
We also noted that, as the duration of computer use increased in patients who underwent kidney transplant, the CPRS-48 behavioral problem scores also increased. In the literature, it has been reported that computer game addiction is associated with behavioral problems.25 Another remarkable issue is that this relationship was not observed in our control group. One interpretation of this situation is that children who are receiving RRT and faced with a situation that challenges their coping systems, such as the difficulties brought by the disease, may be more prone to problems related to screen exposure. Another point that draws attention is our observation that behavioral problems increased as the duration of illness increased in children on dialysis treatment, with depression score increasing as the duration of illness increased in children who had undergone kidney transplantation. In a study conducted in children with chronic diseases such as chronic kidney disease and cancer, depression levels were shown to worsen as duration of illness increased.26 The increased duration of illness may be associated with increased mental disorders due to ongoing treatments and hospitalizations. For this reason, children and adolescents who have been treated for many years should be evaluated in terms of psychiatric disorders.
We noted no studies in the literature that examined screen exposure in patients receiving RRT, such as dialysis and kidney transplant. Based on our current knowledge, this study is the first study examining screen usage characteristics of children receiving RRT. However, this study has some limitations. The first is the limited sample size. Another limitation is the differences in the socioeconomic levels between the RRT group and the healthy control group. No mothers were working in the RRT group, and the mean monthly income of the control group was significantly higher than the RRT group. Studies have shown that children from families with low socio-economic status have more screen time.27 This should also be considered when evaluating the results. In this study, another limitation is that screen times of children and adolescents were evaluated according to answers given by their parents. Parent misrepresentations of past experiences can cause “recall bias,” and parents may not be able to adequately monitor their children’s screen usage. For this reason, as suggested by Barr and colleagues, new studies that use screen time tracking applications will provide more insight on this subject.28
Our results revealed that television watching duration was higher in children and adolescents who received RRT. However, activities such as smartphone and computer use could be associated with anxiety and behavioral problems in children and adolescents receiving RRT. In addition, depression levels increased as duration of illness increased in kidney transplant recipients, and behavioral problem scores increased as duration of illness increased in patients on dialysis treatment. These findings showed that the duration of illness may be associated with mental health problems in children and adolescents receiving RRT. Apart from this, we found that screen usage characteristics of mothers and fathers also affected the screen usage characteristics of children. Children on dialysis or who have undergone kidney transplant are at risk in terms of excessive screen exposure. These children may need to be followed closely for the negative effects of excessive screen exposure. Comprehensive studies with larger sample sizes and that use screen time tracking applications are needed to investigate the characteristics of screen use and its negative effects on this patient group.
Volume : 20
Issue : 3
Pages : 100 - 106
DOI : 10.6002/ect.MESOT2021.P42
From the 1Department of Child and Adolescent Psychiatry, the 2Department of Pediatric Nephrology, the 3Department of Psychiatry; and the 4Department of General Surgery, Division of Transplantation, Baskent University Ankara Hospital, Ankara, Turkey
Acknowledgements: This study was presented as a poster at the 17th Congress of the Middle East Society for Organ Transplantation (MESOT), held virtually on September 3-5, 2021, with partial data presented at the 24th World Congress of International Association for Child and Adolescents Psychiatrists and Allied Professions on December 2-4, 2020, as an oral presentation. The authors have not received any funding or grants in support of the presented research or for the preparation of this work and have no declarations of potential conflicts of interest.
Corresponding author: Hande Ayraler Taner, Ba şkent University Faculty of Medicine, Child and Adolescent Psychiatry Department, Yukar ı Bahçelievler Mah. Şehit Temel Kuğuoğlu Cad. No: 30, Bahçelievler, Ankara, Turkey
Phone: +90 312 2026868
Table 1. Sociodemographic Data (Continuous Variables)
Table 2. Sociodemographic Data (Categoric Variables)
Table 3. Digital Media Tools Owned by Children and Adolescents or Their Families and Their Usage Areas
Table 4. Comparison of Screen Usage Durations and Related Features in Study Groups
Table 5. Data Related to Screen Use and Scores of Assessment Tools Among Study Groups