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Effects of Internet Addiction on Heart Rate Variability in School-Aged Children

Lin, Pi-Chu RN, EdD; Kuo, Shu-Yu PhD, RN; Lee, Pi-Hsia RN, EdD; Sheen, Tzong-Chyi MD, PhD; Chen, Su-Ru PhD, RN

The Journal of Cardiovascular Nursing: November/December 2014 - Volume 29 - Issue 6 - p 493–498
doi: 10.1097/JCN.0b013e3182a477d5
ARTICLES
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Background: The Internet has been gaining worldwide popularity in recent years, but a loss of control over Internet use might lead to negative impacts on our daily lives.

Objectives: This study explored the effects of Internet addiction on autonomic nervous system function through heart rate variability (HRV) analysis.

Methods: This was a cross-sectional design. Data were collected from 240 school-aged children who completed the Chinese Internet Addiction Scale and Pittsburgh Sleep Quality Index questionnaires. Spectral analysis was used to measure HRV. Independent t test was used to compare differences in characteristics and HRV between groups. A 2-way analysis of variance was used to examine group differences in HRV.

Results: Internet addicts had significantly lower high frequency (HF) percentage, logarithmically transformed HF, and logarithmically transformed total power and significantly higher low frequency percentage than did nonaddicts. Internet addicts who had insomnia had higher low frequency percentage and lower HF percentage, logarithmically transformed HF, and logarithmically transformed total power compared with nonaddicts who did not have insomnia.

Conclusions: Internet addiction is associated with higher sympathetic activity and lower parasympathetic activity. The autonomic dysregulation associated with Internet addiction might partly result from insomnia, but the mechanism still needs to be further studied.

Pi-Chu Lin, RN, EdD Associate Professor, School of Nursing, College of Nursing, Taipei Medical University, Taiwan.

Shu-Yu Kuo, PhD, RN Assistant Professor, School of Nursing, College of Nursing, Taipei Medical University, Taiwan.

Pi-Hsia Lee, RN, EdD Professor, School of Nursing, College of Nursing, Taipei Medical University, Taiwan.

Tzong-Chyi Sheen, MD, PhD Doctor, Department of Obstetrics and Gynecology, Yuan’s General Hospital, Kaohsiung, Taiwan.

Su-Ru Chen, PhD, RN Assistant Professor, School of Nursing, College of Nursing, Taipei Medical University, Taiwan.

This study was supported by a grant from the National Science Council of Taiwan (NSC99-2314-B-038-028).

The authors have no conflicts of interest to disclose.

Correspondence: Su-Ru Chen, PhD, RN, School of Nursing, College of Nursing, Taipei Medical University, 250 Wuxing St, Taipei, Taiwan 110 (suru@tmu.edu.tw).

In recent years, the Internet has been gaining worldwide popularity. Online activity offers an immediate source for social interactions, information retrieval, and entertainment. Although the Internet has become an integral part of the daily lives of many people, a loss of control over Internet use might lead to negative impacts on one’s daily life, such as anxiety, depression, or autism.1,2 Among Internet users, teenagers were reported to use the Internet more often than do adults.3–5 In Taiwan, 92% of children aged 12 to 15 years are Internet users.6 Studying problems that can arise from Internet use, especially in children, has become an important public health concern.

Internet addiction usually refers to uncontrollable and damaging use of the Internet.7 Young8 defined Internet addiction as “use of the internet for more than 38 hours per week,” and it was also suggested to be a type of behavioral addiction.9 As the Internet has moved into homes, schools, and Internet cafes, the prevalence of Internet addiction has rapidly been increasing. Internet addiction was suggested to be associated with depression,10 dissociative disorders,11 and attention deficit hyperactivity disorder.12 Besides psychological reliance, Internet addiction was also reported to be associated with physiological symptoms, such as musculoskeletal symptoms of the upper extremity, upper back, and neck.13 Whether Internet addiction is associated with physiological disorders, however, has never been illustrated.

Heart rate variability (HRV) has been widely applied to assess autonomic nervous system function by analyzing the frequency components of oscillation in RR intervals of electrocardiography.14,15 Reduced HRV is associated with various pathological conditions and with increasing morbidity and mortality from cardiovascular disease,16 congenital heart disease,17 and type 1 diat?>betes.18 Reduced parasympathetic activity was also reported in patients with short sleep durations.19 Decreased HRV is associated with a number of risk factors for cardiovascular disease.20 Early detection of changes in HRV can help prevent morbidity and mortality of many disease situations.

Lu et al21 reported that subjects who were at high risk of Internet addiction had stronger blood volume pulse and respiratory response and weaker peripheral temperature and skin conductance, suggesting changes in the autonomic nervous system response in Internet addiction. The HRV in subjects with Internet addiction, however, has never been evaluated. Because Internet addiction inevitably reduces sleep times and disrupts the sleep-wake schedule, it is not surprising that higher rates of insomnia are found among heavy Internet users.22,23 Because children are more vulnerable to Internet addiction than adults are, we designed this study to evaluate the effect of Internet addiction on HRV in school-aged children and to evaluate the concurrent effect from insomnia.

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Methods

Design and Samples

This was a descriptive, cross-sectional design. Subjects aged 10 to 15 years were recruited from a local elementary and junior high school. They were able to read and speak Chinese and were willing to participate in the study. Subjects who had been diagnosed with hypertension, diabetes, cardiovascular disease, or neurological diseases or who were consuming medications such as β-blockers or sedatives that might affect the autonomic nervous system were excluded from the study. Ultimately, 252 subjects were enrolled in the study. Twelve of them failed to complete the test and were excluded from the analysis.

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Instruments

Chinese Internet Addiction Scale

The Chinese Internet Addiction Scale (CIAS) was developed by Chen et al24 in 2003 and has been widely used in Taiwan to assess the behavior of Internet use. The CIAS is a self-administered questionnaire that assesses symptoms of Internet addiction: compulsive use, withdrawal, tolerance, problems with interpersonal relationships, and health/time management. The CIAS consists of 26 items on a scale ranging from 1 (totally agree) to 4 (totally disagree). Scores range from 26 to 104, with higher scores indicating increased levels of Internet addiction. Subjects with a CIAS score of higher than 63 are regarded as having Internet addiction, with a sensitivity of 67.8%, a specificity of 92.6%, and a diagnostic accuracy of 87.6%. The CIAS showed good internal consistency and reliability. Cronbach’s α coefficient was .93, and the test-retest reliability was 0.76.25 In this present study, Cronbach’s α for the internal consistency of the total scale was .80. The 2-week test-retest reliability was r = 0.73 (P < .01).

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Sleep Quality Index

The Pittsburgh Sleep Quality Index (PSQI) was developed by Buysse et al26 in 1989. This self-report questionnaire addresses 7 components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction.26 The sum of scores of 19 items, which falls in the range of 0 to 21, was obtained to assess subjective sleep quality. A PSQI score of higher than 5 is considered indicative of insomnia, with a sensitivity of 98% and a specificity of 55%.26 The Chinese version of the PSQI was translated by Tsai et al27 in 2005, with Cronbach’s α coefficient of .76 and a 2-week test-retest reliability of .70 (P < .01). In the present study, Cronbach’s α for internal consistency of the total scale was .71. The 2-week test-retest reliability was r = 0.70 (P < .01).

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Heart Rate Variability Analysis

To obtain electrocardiographic signals, standard 3-channel electrodes were attached to the anterior chest wall of the subjects and connected to a monitoring system (Acknowledge III, MP150WSW BIOPAC Systems, Santa Barbara, California). All QRS complexes on the electrocardiography were automatically edited and manually corrected by careful inspection of the RR intervals. Signals were digitalized at 500 Hz and transformed into a power spectrum by fast Fourier transformation. The following spectral HRV parameters were obtained for analysis: low frequency (LF; 0.04–0.15 Hz), which represents both parasympathetic and sympathetic functions; high frequency (HF; 0.15–0.4 Hz), which represents parasympathetic function; and total power (TP; <0.4 Hz), which represents the overall autonomic nervous system function.28 Low frequency and HF were further normalized by the percentage of TP except for very LF (<0.04 Hz) to detect the sympathetic (LF%) and parasympathetic (HF%) influences on HRV. Low frequency, HF, and TP were logarithmically transformed (Ln) to control for the skewed distributions.

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Ethical Considerations

Before researchers contacted participants, the relevant institutional review board approved the study. One researcher contacted participants to verbally explain the study and mail the contents to their parents. All participants and their parents provided written informed consent before being allowed to participate in the test. All participants were told that they could withdraw from the study at any time without penalty and that all information would remain confidential. After participants completed the questionnaires and HRV test, they received a small gift as a token of our appreciation.

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Data Collection Procedures

Data were collected between February 2010 and May 2011. Participants who met the inclusion criteria received a formal oral description of the study purpose, procedures, and instruments. All participants were asked to fill out the demographic information and CIAS and PSQI questionnaires. If participants have questions about the items, the researcher would explain the meaning of items to help complete the questionnaires. An HRV analysis was then performed. All measurements were performed in the morning and under controlled conditions; the room temperature was controlled to 24°C to 28°C. Participants were told to avoid vigorous exercise and caffeinated beverages for 2 hours before testing. Subjects were placed in a supine position with chest electrodes connected, breathed normally, and were allowed to rest for 15 minutes before beginning the test. Electrocardiography was used to continuously monitor the heartbeat throughout the procedure, and 5‐minute steady-state electrocardiography recordings were obtained for analysis of HRV.

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Data Analysis

Data were analyzed using SPSS 19.0 (SPSS, Chicago, Illinois). Descriptive statistics such as frequency, range, mean, and standard deviation were used to present the sample demographics. Independent t test was used to compare differences in characteristics of HRV between Internet addiction and Internet nonaddiction. A 2-way analysis of variance with Internet addiction and insomnia serving as the main factors was used to examine group differences in HRV. A P value of < .05 was considered statistically significant.

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Results

Characteristics of the Sample

In total, 240 subjects (129 boys and 111 girls) were recruited for the analysis, and 37.9% of them were from single-earner families and the others were from dual-earner families. The mean age was 12.3 ± 1.7 years, and the mean body mass index was 19.3 ± 2.5 kg/m2. The mean sleep quality was 4.8 ± 2.9.

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Effect of Internet Addiction on Heart Rate Variability

On the basis of a CIAS cutoff score of 63 of 64, all subjects were classified as either an Internet addict (n = 55) or nonaddict (n = 185). Age, educational levels, body mass index, and family economic status did not significantly differ between Internet addicts and nonaddicts. The percentage of male subjects (74.5% vs 47.5%; P < .001) and the mean sleep quality score (6.6 ± 2.4 vs 4.2 ± 2.9; P < .001) were higher in Internet addicts than in nonaddicts (Table 1).

TABLE 1

TABLE 1

The HRV parameters were compared between Internet addicts and nonaddicts. Results showed that Internet addicts had significantly lower HF% (36.1 ± 14.9 vs 46.9 ± 14.8; P < .001), LnHF (4.9 ± 1.2 vs 5.6 ± 1.1; P < .0001), and LnTP (6.4 ± 0.9 vs 6.9 ± 0.8; P = .001) and a significantly higher LF% (64.0 ± 14.9 vs 53.1 ± 14.7; P < .001) compared with nonaddicts. No significant difference, however, was found in LnLF (5.7 ± 0.9 vs 5.8 ± 0.8; P = .06) between the 2 groups (Table 2).

TABLE 2

TABLE 2

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Effects of Internet Addiction and Insomnia on Heart Rate Variability

To study the concurrent effects of Internet addiction and insomnia on HRV, subjects were categorized into 4 groups: insomnia/Internet addicts group (n = 39), insomnia/Internet nonaddicts group (n = 54), noninsomnia/Internet addicts group (n = 18), and noninsomnia/Internet nonaddicts group (n = 129). Results of the 2-way analysis of variance revealed a significant interaction between Internet addiction and insomnia on LnHF (F1, 236 = 5.59, P = .02) and LnTP (F1, 236 = 7.38, P = .009). Post hoc analysis of the cell means among the 4 groups indicated that the insomnia/Internet addicts group had significantly lower LnHF (4.8 ± 1.2 vs 5.7 ± 1.1; P < .0001) and LnTP (6.3 ± 0.8 vs 6.9 ± 0.8; P = .005) compared with the noninsomnia/Internet nonaddicts group and a significantly lower LnHF (4.8 ± 1.2 vs 5.5 ± 0.9; P < .0001) compared with the insomnia/Internet nonaddicts group. There were significant main effects for Internet addiction on LF% (F = 17.3, P < .001), HF% (F = 16.7, P < .001), LnHF (F1, 236 = 11.3, P = .001), and LnTP (F1, 236 = 5.8, P= .01). The Internet addicts groups tended to have a higher LF% and lower HF%, LnHF, and LnTP than the Internet nonaddicts groups did. No other statistically significant differences in HRV were found between the Internet addicts groups and Internet nonaddicts groups. There was a significant main effect for insomnia on LnTP (F1, 236 = 4.4, P = .03). The insomnia groups tended to have a lower LnTP than the noninsomnia groups did. No other statistically significant differences in HRV were found between the insomnia groups and noninsomnia groups (Table 3).

TABLE 3

TABLE 3

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Discussion

Few studies have reported on autonomic nervous function in Internet addiction. Through HRV testing, our results suggest that school-aged children with Internet addiction have higher sympathetic activity and lower parasympathetic activity and overall autonomic activity. The results confirmed the report of Lu et al21 that the sympathetic nervous system is highly activated with Internet addiction. In their series, a stronger blood volume pulse and respiratory response and a weaker periphery temperature were observed in high-risk Internet addiction abusers.21 Our results that Internet addiction was associated with lower parasympathetic activity, however, contradicted the finding of Lu et al that the skin conduction index was lower in high-risk Internet abusers. This disagreement could have result from the different methods used to measure parasympathetic activity or the aversive stimuli from Internet use that Lu et al reported in 18- to 24-year-old Internet users, which are likely seldom encountered by school-aged children.

Because Internet addiction may alter the sleep-wake schedule,29 it is not surprising that a higher rate of insomnia was found among Internet addicts in our study. Excessive Internet use may deprive one of sleep time and adversely affect the mental and physical health of adolescents.30 Adverse effects of poor sleep quality on autonomic nervous system function were reported. Zhong et al31 demonstrated that acute sleep deprivation was associated with decreased parasympathetic activity and increased sympathetic activity in subjects aged 18 to 40 years.

Spiegelhalder et al19 reported that in adult subjects with objectively reported insomnia, reduced parasympathetic activity and decreased HRV were demonstrated through an HRV analysis. Our results showed that no matter whether subjects had insomnia or not, the HRV of Internet addicts was worse than that of nonaddicts. The increased sympathetic activity and decreased parasympathetic activity were observed when Internet addiction was associated with insomnia, suggesting that the adverse effects of Internet addiction on the autonomic nervous system function may partly result from insomnia.

Internet addiction was reported to be associated with depression.10 In a meta-analysis based on 18 articles comprising 673 depressed participants and 407 healthy controls, authors concluded that the decreasing of HRV was associated with the severity of depression.32,33 Subjects with Internet addiction tend to consume more coffee and cigarettes that are simulative. Both active smoking and passive smoking were demonstrated to increase sympathetic drive and reduce HRV and parasympathetic modulation.34 Conversely, modest amounts of caffeine were reported to enhance parasympathetic activity, with a concomitant reduction in sympathetic activity in healthy volunteers and individuals with type 1 diabetes.35 A sedentary lifestyle associated with Internet addiction was also reported to decrease HRV. The influence of Internet addiction on autonomic nervous system function might be composite effects of psychological, physiological, and behavioral changes that accompany Internet overuse. The mechanism of autonomic nervous activity dysregulation associated with Internet addiction still needs to be further elucidated.

There were limitations of the present study. First, because this study was a cross-sectional study, we could not confirm causal associations among Internet addiction, insomnia, and the autonomic nervous system. Second, the assessments of Internet addiction and insomnia were based only on the self-reported perspectives of teenagers. If participants denied or could not estimate their maladaptive Internet addiction, then Internet addiction would be underestimated.

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Conclusions

Internet addiction is associated with higher sympathetic activity and lower parasympathetic activity. The autonomic dysregulation associated with Internet addiction might partly result from insomnia, but the mechanism still needs to be further studied.

School-based health programs should consider incorporating Internet use as part of routine assessments.

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What’s New and Important

  • School-aged children with Internet addiction have higher sympathetic activity and lower parasympathetic activity and overall autonomic activity.
  • A higher rate of insomnia was found among Internet addicts than in nonaddicts, and the adverse effects of Internet addiction on the autonomic nervous system function may partly result from insomnia.
  • The influence of Internet addiction on autonomic nervous system function might be composite effects of psychological, physiological, and behavioral changes that accompany Internet overuse.
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Acknowledgments

The researchers express their sincere appreciation to the participants who generously shared their experiences and took time to complete the survey.

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Keywords:

heart rate variability; Internet addicition; school-age children

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