Overall our findings suggest a paucity of empirical studies addressing PIU among populations of US adolescent and college student populations. Despite initially finding over 600 search hits on the topic of PIU, only 18 articles were identified that met inclusion criteria, less than half of these reported a prevalence estimate. We found no studies specifically targeting adolescent populations.
Among these studies, the overall quality scores were very low. Many of the QRT items that received particularly low scores, such as using a validated instrument and reporting missing data, have significant impact on the internal validity of the findings. Further, other areas that received low scores, such as reporting response rates and participant characteristics, critically impact the external validity of these studies. Future studies of PIU could consider using the STROBE criteria or our QRT to enhance the quality of the study and thus the validity of the findings.
The studies examined in this review reported prevalence rates ranging from no participants meeting criteria to up to a quarter of participants meeting criteria for PIU. There are several possible reasons that this range of reported prevalence rates is so wide. First, many of these instruments applied vastly different conceptual approaches based on addictions such as substance use or gambling, or other cognitive, behavioral or impulse-control models. The lack of consensus in conceptual approach to PIU may be a key reason for the variability amongst these studies approach and findings. Second, perhaps related to the lack of consensus on the appropriate conceptual approach to PIU, the majority of studies in this review used independently created instruments whose conceptual framework is incompletely evaluated. This then leads to additional challenges because the psychometric properties of these new instruments are often incompletely evaluated. Third, instruments used to evaluate PIU applied varying response mechanisms: some used Likert scales which allow for reporting the degree and severity of symptoms or consequences, and others used binary “yes/no” responses which may not fully capture the frequency or severity of a problematic behavior. Fourth, the cut-offs for criteria defining the when a participant met criteria for PIU varied among the instruments used to assess PIU. As studies did not correlate their cut-points to actual negative consequences such as behavioral or achievement problems, it is difficult to know whether participants who were labeled as having PIU were actually experiencing any offline consequences.
Last, over half of the studies reporting prevalence estimates were conducted over five years ago during a time where wide-scale internet use was still varied and growing. Immense changes in both internet access and use have occurred over the last decade.1
Thus, it is reasonable to assume that not only the extent of, but also the populations most at risk for, internet addiction may have changed from what was evident in the past. More recent work is required to determine not only a current estimate of prevalence based on a standardized approach, but also what characteristics may put an individual at increased risk in our current technology-saturated culture. Findings which are informed by current internet use standards and trends may also help to shape the development and definition of a diagnosis for a clinical disorder.
The findings in this review may be limited as we did not search the gray literature (evaluation of theses, dissertations or unpublished work). However, many of the studies examined in our review had methodological flaws limiting external validity, such as failure to report response rates, thus the gap between unpublished and published literature may be small. Further, given the newness of this field and the wide range of prevalence rates reported in studies, including studies that reported a prevalence rate of 0%, it is likely that publication bias may also be small. Our goal in this study was to evaluate US studies, thus, generalization beyond the US is not warranted.
Despite these limitations, our study findings illustrate the critical need for additional rigorous study of PIU. However, in order to fully understand and estimate the impact of this new disorder, we must first have consistency and consensus in the approach to its assessment. Among the instruments identified in this study, the IAT was the only validated instrument used in a study that reported prevalence rates. Another validated and frequently used instrument was the OCS, although this scale was not used in studies reporting prevalence data. Thus, these instruments may be a useful starting point for future study. As both of these measures were initially developed over 8 years ago, re-evaluating their construct structure and establishing face validity in the context of today’s internet-rich environment and within this target population will be an important initial step. Administering multiple instruments in the context of a single study to determine overlap and concurrent validity may be useful in the pursuit of developing a comprehensive instrument to assess PIU. Following this, further rigorous studies using a validated instrument and incorporating recognized quality criteria may be conducted to confirm prevalence data. Finally, among studies that reported time spent on the internet, all relied upon participant self-report for cumulative internet use. Future studies that provide more accurate means of measuring internet use are needed.
Further, of note, no US studies identified in this review included samples focused on the adolescent population, and studies of college students were generally limited to a single university and modest sample sizes. Future large-scale studies within these at-risk populations are urgently needed to confirm and enhance generalizability. Several European and Asian countries have included assessments of internet addiction within national assessments of adolescent and college student health.10, 28, 65, 66
Adopting similar methods within the US may allow for accurate identification and estimated scope of this problem on a national level.
If internet use has potential to lead to addiction, this means that up to 93% of US adolescents and young adults are exposed to this risk, dwarfing exposure rates for any other behavioral or substance-based addiction.1
Before we can fully understand this important phenomenon, we must first have consistency and consensus in the approach to its assessment. Only after these studies have firmly established current prevalence and considered risk factors, can we make informed considerations on what diagnostic criteria should be recommended for inclusion within the DSM or how to evaluate the successes of any proposed treatment programs.