Gender-related differences in the relationship between problematic and pathological Internet use and self-reported sleep-wake habits among university students
F. Canan1,2, S. Karaca2, M. Toprak1, M. Kuloğlu2, M.N. Potenza1,3,4,5
1 Department of Psychiatry, Yale School of Medicine, New Haven, CT, 06510, United States
2 Department of Psychiatry, Akdeniz University School of Medicine, Antalya, Turkey
3 The National Center on Addictions and Substance Abuse, Yale School of Medicine, New Haven, CT, 06510, United States
4 The Connecticut Mental Health Center, New Haven, CT, 06519, United States
5 Department of Neuroscience and Child Study Center, Yale School of Medicine, New Haven, CT, 06510, United States
Department of Psychiatry, Akdeniz University School of Medicine, 07059, Antalya, Turkey
Phone: +90 (242) 2274400
Fax: +90 (242) 2275540
Objectives: Gender differences have been observed in objective and subjective sleep measures. Problematic Internet use is associated with poor sleep. This study, considering genders separately, examined the relationship between sleep/wake variables and problematic and pathological Internet use among university students. Methods: We recruited 661 undergraduate students (382 females and 287 males). Reports on habitual bedtimes and wake times for weekdays and weekends were used. Internet Addiction Test (IAT) was used to assess problematic and pathological Internet use (PPIU). Results: PPIU was associated with delayed bedtime and wake time on weekends but not with less sleep duration both on weekdays and weekends among females. For males, PPIU was only related to delayed bedtime on weekends Compared to males with adaptive Internet use (AIU), those with PPIU had shorter weekday and weekend sleep durations. Weekday and weekend sleep durations correlated negatively with IAT scores among males, but not among females. IAT scores were independently associated with sleep duration among males. Conclusions: Our findings expand the literature by documenting gender-related differences on the relationship between PPIU and sleep. We propose that young males with PPIU are more likely than females with PPIU to exhibit shortened sleep duration.
Bedtime; gender; Internet addiction; sleep; wake time
Excessive electronic media use is associated with various adverse consequences including diminished academic performance (1), sedentary behavior (2), obesity (3), emotional and behavioral problems (4), depression/anxiety symptomatology, and disturbed general well-being (5). Inordinate amount of time spent on electronic media use is also related with sleep problems such as delayed bedtime and shorter total sleep (6).
Because of a multitude of intrinsic and environmental factors, younger adults (especially university students) are particularly vulnerable to disturbed sleep, and are one of the most sleep deprived age groups (7). In addition, younger adults are likely to use newer electronic media forms (Internet, smartphone, etc.), rather than conventional ones such as television, book, music, and films (8). For instance, young American adults (aged 18-29 years) were found to be engaged in Internet activities to a significantly larger extent than they were engaged in television viewing (9). Thus, it is important to explore the association of maladaptive Internet use and sleep problems, particularly in young adults.
The intuitive belief that Internet use is associated with sleep problems has long been accepted (10). The relationship between problematic and pathological Internet use (PPIU) and sleep problems, however, has not been extensively studied (11). Cross-sectional studies, conducted on adolescents and young adults, have shown that when individuals with PPIU were compared with adaptive Internet users (AIU), they took longer to fall asleep, had more frequent night awakenings, had less total sleep time, and felt sleepier during the daytime (12-15). Moreover, a 1-year longitudinal study (16) examined the bidirectional relationships between sleep problems and PPIU among children and adolescents and found that sleep problems sequentially predicted PPIU, and PPIU sequentially predicted disturbed circadian rhythm. Despite the gender-related differences in sleep patterns, which become apparent after the onset of puberty (17), previous work has not examined the relationship between sleep problems and PPIU, considering genders separately.
Our goal was to investigate whether PPIU would affect bedtime and wake time, as well as sleep duration among undergraduate students. We also aimed to examine whether the relationship between PPIU and sleep-wake habits would differ depending on gender.
Materials and Methods
This was a cross-sectional study. The target population was undergraduate students at the main campus of a large public university located on the southern Turkey. A convenience sample of 694 students were recruited. This study is a part of a broader research effort aimed at the examination of addictive disorders and their relations to various factors among undergraduate students. Participants were recruited through classes, personal contact, fliers, and a student volunteer subject pool. Data collection took place over a period of 20 weeks (from January 1, 2016, to May 31, 2016). Individuals were not offered any compensation for their participation. After excluding students with incomplete data, the final analyzed sample consisted of 669 students.
The study was approved by the local research ethics committee. Signed consent was obtained from all participants
A questionnaire, developed by the authors, collected information about sociodemographic characteristics, weight, height, sleep, alcohol and nicotine use patterns, and Internet use habits. Sleep-related questions were “What time do you usually go to bed on a typical school day?”, “What time do you wake up on a typical day that you have to go to school?”, “What time do you go to bed on a typical weekend day?”, and “What time do you wake up on a typical weekend day?”. Hours were counted not in AM and PM but from 0 to 24. Sleep duration was calculated from bedtime and wake time. Current psychiatric treatment was inquired with the question: “Have you been diagnosed as having any psychiatric disorder by a clinician during the past six months?”. Frequency of alcohol use over the past six months was assessed using a Likert response format (0 = never, 1 = three times a month or less, 2 = once a week, 3 = a few times each week, 4 = every day). Students were also asked how often they smoked cigarettes over the past six months (0 = never, 1 = irregularly/not daily), 2 = regularly/daily).
Internet Addiction Test (IAT): We used the IAT (18) to evaluate PPIU. The IAT is one of the most widely used instruments for the assessment of maladaptive Internet use. It does not identify the specific Internet applications (e.g., online gaming, using the Internet for sociability, pornography) which are problematic. The IAT is self-administered and uses a Likert scale with response categories ordered from “0 = Does not apply” to “5 = Always”. It includes 20 items, and the total score can range from 0 to 100, with scores of 49 or lower indicating that the individual has adaptive Internet use (AIU), 50 or higher indicating that the individual has problematic Internet use and 80 or higher indicating that the individual has pathological Internet use (33). The internal consistency of the Turkish version of the IAT was found to be high (Cronbach’s alpha coefficient = 0.93) in a Turkish undergraduate sample (19).
We used IBM SPSS Statistics software version 20.0 (Armonk, New York, USA) to perform statistical analysis. Student`s t test was used for continuous variables (i.e., age, BMI) to assess between-group differences (e.g., females vs males). The Mann-Whitney U test was used as appropriate for comparisons between non-normally distributed variables, including bedtime, wake time, and sleep duration. Continuous variables were presented as the mean or median and standard deviation (SD) or interquartile range (IQR), whichever appropriate. The chi-square test was used to compare proportions between the groups. Spearman correlation coefficients were calculated to study the associations between sleep parameters and other variables. A multiple linear regression analysis was performed to identify independent predictors of weekday and weekend sleep durations. Statistical significance was set at a p value of less than 0.05.
The sample consisted of 382 females (57.1%) and 287 males (42.9%). The mean age of participants was 20.7 years (range, 17-27). On a typical weekday, the students` medians for bedtime and wake time were 23:30 (IQR, 1.5 hours) and 07:30 (IQR, 1.5 hours), respectively. The medians for bedtime and wake time were 00:30 (IQR, 1.25 hours) and 09:30 (IQR, 1.5 hours), respectively, during a typical weekend day. The prevalence of problematic and pathological Internet use in the total sample was 13% and 2.8%, respectively. The low frequency of pathological Internet users necessitated the combination of the problem and pathological groups (with PPIU) that was used for the analyses reported below. The median time spent online on a typical weekday was 3 hours (IQR, 2) and that on a typical weekend day was 4 hours (IQR, 2).
As shown in Table I, at the bivariate level, females were younger, had lower BMI, went to bed earlier and woke earlier, had lower IAT scores, and had lower rates of sleeping after midnight during weekdays than males.
Because of the significant differences found in sleep patterns between males and females, we reanalyzed the findings for both sexes separately. Table II demonstrates the comparison of females with PPIU and AIU and that of males with PPIU and AIU.
Table II. Comparison of females/males with and without PPIU.
Spearman`s correlation analysis revealed that duration of the Internet use had significant and positive relationships with weekday/weekend bedtime and weekday/weekend wake time among females and males (Table III). However, weekday/weekend sleep duration correlated negatively with IAT scores in males only.
Table III. Spearman correlation coefficients for sleep parameters and other variables.
Compared to males with AIU, a higher proportion of males with PPIU reported Internet gaming as their most frequent Internet activity (8.2% vs 51.9%, χ2 = 61.127, p < 0.001). Male students who used the Internet mostly for gaming reported shorter weekend sleep durations than those who used the Internet for other activities (e.g., social networking, streaming videos) (Table IV).
For males, a multiple linear regression was undertaken to examine variance in sleep durations. Age, BMI, IAT score, duration of Internet use on a typical weekday (for weekday sleep), duration of Internet use on a typical weekend day (for weekend sleep), having current psychiatric disorder, and frequencies of alcohol and nicotine use were loaded into the model as predictors. Only IAT score was significantly associated with decreased weekday (β = -0.171, t = -2.650, p = 0.009) and weekend sleep (β = -0.159, t = -2.314, p = 0.021).
The main findings of this study are that (i) female students and male students exhibited significantly different bedtime and wake time although they had comparable sleep durations; (ii) females with PPIU had similar sleep durations to those with AUI; (iii) compared to males with AIU, those with PPIU had shorter weekday and weekend sleep durations; (iv) weekday and weekend sleep durations correlated negatively with IAT scores among males, but not among females; and (v) for males, IAT scores were independently associated with sleep duration.
Our findings that female university students went to bed and rose earlier than males are in good agreement with previous studies (20-22). The existence of sex-related differences in sleep and circadian timing has been interpreted as the product of both biological factors (e.g., sex hormones) (23) and behavioral influences (e.g, males have higher screen times -television, videogame and Internet use- than females) (24).
We found that PPIU was associated with later bedtime and wake-up time on weekends but not with less sleep duration both on weekdays and weekends among females. For males, however, PPIU was only related to later bedtime on weekends. In addition, males with PPIU had shorter sleep durations both on weekdays and weekends when compared with males with AUI. Moreover, the relationship between PPIU and shorter sleep duration was not affected by the time spent online. This result is in line with that of Custers and Van den Bulck (25), showing that the total duration of Internet use was not a significant and independent predictor of reduced sleep window or tiredness among Belgian adults. Our findings may imply that PPIU leads to changes in weekend sleep-wake patterns without affecting sleep duration in female students. In contrast, males with PPIU tend to exhibit a decrease in sleep duration with no shift in their sleep-wake schedule.
Use of electronic media (television viewing, use of computers/mobile phones, video/Internet gaming) has been hypothesized to cause a broad spectrum of sleep problems via replacing sleep (26), causing heightened alertness and arousal (27), or bright light exposure affecting the sleep/wake cycle through suppression of the secretion of melatonin (28). In our study, bedtime and wake time hours were positively correlated with the duration of Internet use, which may be related with all the mentioned hypotheses. However, the finding that the association between higher severity of Internet addiction and shorter sleep duration was independent from the duration of Internet use supports the ‘increased arousal’ hypothesis rather than the ‘replacement of sleep’ and the ‘bright light exposure’ hypotheses in males. Thus, even though Internet use effects the sleep patterns of both females and males, the influence of PPIU on sleep seems to differ across genders. According to our findings, we propose that males are more prone to PPIU-related sleep problems.
Internet-gaming disorder, which has been included in the section III of the DSM-5 (29), is one of the main types of problematic Internet-use behavior and is associated with significant adverse consequences (30). In the current study, males with PPIU were more likely to report gaming as their most frequent Internet activity. Although we did not assess Internet-gaming disorder by a validated instrument, online gaming activity may be considered as the one most likely to be related to PPIU in this population. We found that males whose most frequent online activity was Internet gaming exhibited later bedtime on weekdays and weekends, later wake-up times on weekends, and had reduced sleep on weekends when compared with those who used the Internet most frequently for other online activities. Internet gaming disorder has previously been shown to be associated with poorer quality of sleep (11). According to our findings, a specific type of Internet addiction, namely Internet-gaming disorder, might be most closely related to later bedtimes and shorter duration of weekend sleep among males. However, studies directly focusing on Internet-gaming disorder should be conducted in order to draw more definitive conclusions.
This study, we believe, is the first to assess sex-related differences in the association of PPIU and sleep-wake habits. Additionally, our sample size was relatively large. Several limitations, however, should be kept in mind when interpreting the findings of this study. The cross-sectional design of the study hinders providing a causal relationship between PPIU and sleep variables. Reverse causality might occur because students who need less sleep or have trouble sleeping for other reasons may choose to spend their time in the Internet simply because they have more time to do so (31). We recruited a convenience sample which was drawn from a single university. Thus, participants may not be representative of all university students or the general population. Since our results rely on self-report data, a potential report bias could not be ruled out. We did not use validated instruments such as Pittsburgh Sleep Quality Index, Morningness–Eveningness Questionnaire, or Epworth Sleepiness Scale in the assessment of sleep and related factors. We assessed PPIU by use of a standardized self-report instrument rather than by a diagnostic interview. Because of the relatively small number of individuals with pathological Internet use, we could only examine differences related to PPIU as a whole. Lastly, we did not evaluate other possible confounding factors such as depression (13), which could affect relationships between PPIU and sleep variables.
According to our findings, female university students with PPIU has significantly delayed sleep-wake schedule on weekends, but similar total sleep time throughout the week when compared with those with AIU. Male students with PPIU, however, are more likely to sleep less in comparison to their counterparts, without a significant delay in their sleep-wake habits. Moreover, Internet addiction is independently associated with shorter sleep duration when other factors such as the duration of Internet use and alcohol or nicotine consumption were considered among males. Our results expand the literature by documenting gender-related differences on the relationship between PPIU and sleep. We propose that young males with PPIU are more likely than females with PPIU to exhibit shortened sleep duration. Taking into account the gender differences and considering limitations mentioned above, further well-designed studies should prospectively evaluate the association of sleep and PPIU.
Funding sources: Author Marc N. Potenza’s involvement in this work was supported by the National Center on Addiction and Substance Abuse and a Center of Excellence in Gambling Research Award from the National Center for Responsible Gaming. The funding agencies had no role in study design; data collection, analysis and interpretation; preparation of the manuscript; or the decision to submit the paper for publication.
Acknowledgements: The authors thank Dr. Melike Düzgün, Dr. Ayşe Merve Erdem, Dr. Esranur Karaçaylı, and Dr. Nur Begüm Topan for their help in data collection.
Conflicts of interest: Authors Fatih Canan, Servet Karaca, Mesut Toprak, Murat Kuloğlu, and Marc N. Potenza declare that they have no conflict of interest with respect to the content of this manuscript.
Author Marc N. Potenza has: consulted for and advised Lundbeck, Ironwood, Shire, INSYS Rivermend Health, Opiant/LightlakeTherapeutics and Jazz Pharmaceuticals; received research support from the National Institutes of Health, Veteran’s Administration, Mohegan Sun Casino, the National Center for Responsible Gaming and its affiliated Institute for Research on Gambling Disorders, and Pfizer; participated in surveys, mailings, or telephone consultations related to drug addiction, impulse control disorders or other health topics; consulted for law offices and the federal public defender’s office in issues related to impulse control disorders; provides clinical care in the Connecticut Department of Mental Health and Addiction Services Problem Gambling Services Program; performed grant reviews for the National Institutes of Health and other agencies; has guest-edited journal sections; given academic lectures in grand rounds, CME events and other clinical/scientific venues; and generated books or chapters for publishers of mental health texts. Other authors report no disclosures. The views presented in this manuscript represent those of the authors and not necessarily those of the funding agencies who had no input into the content of the manuscript.
Cite this article as
Canan, F. Karaca, S. Toprak, S.M. Kuloğlu, M. Potenza, M.N. (2019). Gender-related differences in the relationship between problematic and pathological Internet use and self-reported sleep-wake habits among university students. Archives of Behavioral Addictions, 1(1). doi: 10.30435/ABA.01.2019.03
This study shows that there are gender-related differences on the relationship between PPIU and sleep problems. PPIU is associated with shorter sleep duration, particularly in male university students.
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