Children are growing up in environments that have become increasingly saturated with various digital devices. According to a 2020 report on media use of children aged 0 to 8 years in the United States [1], 46% of those aged 2 to 4 years and 67% of those aged 5 to 8 years own a mobile device (ie, tablet or smartphone). The average daily screen time is 2.5 hours for children aged 2 to 4 years and 3.1 hours for those aged 5 to 8 years. The same data show that many children are being regularly exposed to screens even earlier; on average, they spend 49 minutes per day looking at a screen in the first 2 years of their lives. In addition, most of this screen use occurs in the absence of parents, with the likelihood of parental coviewing drastically decreasing with increasing age. The data also show that nearly three-quarters of screen time is spent watching video content, while reading, homework, and video chatting represent only 5% of children’s screen time. Furthermore, the data from the United Kingdom confirms that children in the United Kingdom are no exception since 48% of those aged 3 to 4 years and 57% of those aged 5 to 7 years owned a tablet in 2020, while 90% of those aged 3 to 4 years and 88% of those aged 5 to 7 years watched video-on-demand content [2].

Many stakeholders have expressed concerns about the potential harms associated with excessive screen use in early childhood. In 2016, the American Academy of Pediatrics issued a policy statement concerning media use in early childhood [3], recommending that children aged <18 to 24 months avoid digital media altogether. They argued that children aged <2 years require “...hand-on exploration and social interaction with trusted caregivers to develop their cognitive, language, motor, and socio-emotional skills,” while they cannot learn from traditional digital media in the same way. They stated that children aged 2 to 5 years should limit screen use to 1 hour per day of high-quality screen time, coviewed by parents to help them understand what they are seeing. The guidelines on screen use in children, published in other countries (eg, World Health Organization guidelines [4], Canadian guidelines [5], and Indian guidelines [6]), mostly followed the daily screen time limit recommendations for each age group.

However, the screen time restriction approach has been criticized, as many researchers and experts [7] argue that the existing scientific evidence is not conclusive enough to suggest appropriate amounts of screen use or preferable web-based activities for children of different ages. A brief look at systematic literature reviews on the effects of screen exposure on various outcomes in those aged 0 to 6 years reveals largely correlational evidence of the effect on adiposity, obesity, or BMI [8-10]; cognitive development [8,11]; psychosocial health [8]; and sleep duration [10]. However, to our knowledge, this evidence is yet to provide support for the suggested thresholds above which screen time is reliably detrimental to children. In a large study on 19,957 parents of children aged 2 to 5 years, authors found no empirical support for well-being benefits for children following the American Academy of Pediatrics screen time recommendations [12]. Researchers have argued that screen time, defined as the duration of exposure to digital devices, misses the content and context of digital technology (DT) use and is likely too broad and simplistic to be used as a stand-alone measure [13-15].

Owing to the shortcomings of screen time, the concept of problematic media use, defined as “...excessive use that interferes with the child’s functioning” [16], has gained momentum in the scientific community (eg, [17-19]). The focus on impairments in functioning is crucial to differentiate normal variation from a pathological level of behavior [16]. First, while we concur with the emphasis on functioning impairments, we will instead be referring to problematic DT use (PDTU), since the term “media” can also refer to traditional means of communication (eg, newspaper and radio) or collective institutions engaged in mass communication [20], both of which are erroneous interpretations of the concept. Second, we emphasize that although interference with functioning can certainly happen due to “excessive use” of DT, both the content and context of children’s DT use are arguably just as problematic. Thus, we suggest defining PDTU as any pattern of DT use that interferes with the child’s functioning.

Although the importance of content and context may seem rather obvious, contemporary research practices implied otherwise; a systematic review of 622 screen use measures in children aged 0 to 6 years [21] found that only 10.8% of these measures considered content and only 7% considered coviewing (ie, a measure of context). Importantly, this preference for exposure measures does not extend to older children and adolescents; a scoping review of empirical studies published between 2014 and 2019 by Browne et al [22] identified 162 measurement tools of DT use in children, adolescents, and young adults, most of these targeting problematic or excessive and addictive use beyond exposure. Among the 162 identified tools, only 5 were intended for preschool children, 3 of which came from gray literature. Evidently, despite many public concerns about harms associated with early DT use, most established and validated measuring tools of PDTU are intended for adolescents or adults, while instruments for young children are substantially less common. More recently, a systematic review by Rega et al [23] aimed to identify PDTU measures for children aged <10 years and found 9 parent report measurement tools aimed at children aged <6 years but did not analyze their content or psychometric properties. In conclusion, the various ways in which researchers have attempted to measure problematic media use in young children have not yet been critically reviewed and synthesized. In our view, this procedure is absolutely necessary to eventually arrive at comprehensive, valid, and cost-effective measures for children’s PDTU, which itself is a prerequisite for effective screening, prevention, and treatment of at-risk children.

On the basis of these insights, we aimed to review existing empirical studies, which included measures of PDTU in early childhood (ie, children aged 0 to 6 years) beyond screen time. Since our primary objective was to list and describe the various existing measures and operationalizations of the proposed concept (ie, PDTU) rather than answering a specific research question, we opted for a scoping review rather than a systematic review. The idea was to describe each measure or instrument in terms of its content, psychometric properties, and the negative outcomes it could lead to based on the results of each included study. Ideally, the goal was to arrive at a set of measures of PDTU for young children, which are psychometrically sound (ie, reliable and valid) and shown to be related to certain undesirable outcomes (eg, behavioral or emotional problems, deficiencies in terms of development, health, and well-being). Finally, we aimed to search beyond the developed measurement tools, seeking to identify the various single-item measures used by researchers to assess particular PDTU practices in preschool children.

This study followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) protocol [24]. The final version of the protocol was agreed upon by all authors and was not preregistered.

The publications considered for review had to meet the following requirements: (1) peer-reviewed scientific publications; (2) published within the past 12 years (studies dating from January 1, 2012, to December 20, 2023); (3) written in the English language; (4) describing an empirical study; (5) including a measure of PDTU; and (6) conducted with the population of young children aged 0 to 6 years.

In addition, studies, which conceptualized and measured PDTU solely in terms of screen time, were excluded for reasons put forth in the Introduction section. Similarly, questions about which digital devices a child uses and to what extent (eg, minutes of use per day for each device type) were deemed overly simplistic, experiencing the same drawbacks as screen time. Finally, questions about the content the child usually engages in and to what extent (eg, minutes per day for each content type) were also not considered to be sufficient measures of PDTU. This is partly due to the vast variability of potential user experience that exists within a single content category (ie, “educational” content, video games, and cartoons). Furthermore, our concern was that due to the rapid evolution of content, any findings about the extent of the “problematic nature” of certain content types would likely soon be out of date (ie, as noted by Viner et al [25]).

The search for relevant publications was conducted in the Web of Science, PubMed, and Google Scholar databases. Each of these databases was last searched on December 20, 2023.

The final search strategy consisted of 4 groups of keywords, separated by the Boolean operator AND (Table 1). Each keyword group refers to a certain concept, which may be represented by any of the listed keywords, separated by the Boolean operator OR. In addition, filters for the date of publishing (ie, January 1, 2012, to December 20, 2023) and language (ie, the English language) were applied to all searches.

In each database, the final search strategy was applied only to titles and abstracts, as opposed to full texts, of published records. In the case of Google Scholar, a simplified search strategy was used due to the character limit, containing only the most common keywords for each of the 4 concepts. We developed the version of the search strategy with our backgrounds in psychology and psychometrics. Afterward, we scanned the records obtained, and the search strategy was adjusted accordingly. The adjustments mainly consisted of adding new keywords for each concept and adjusting the existing keywords (eg, shortening phrases to include alternative expressions). After multiple iterations, we derived the final search strategy, which yielded a manageable number of seemingly relevant publications in all databases.

All publication titles from the list of unique records were screened by 1 researcher using the inclusion and exclusion criteria. If eligibility was unclear based on the title, the abstract was read. When ambiguity remained (eg, age of children not specified), the publication was included for full-text review. In case of dilemmas, other authors were consulted, and disagreements were resolved collectively.

When screening titles, we included records mentioning the use of DTs of some kind (eg, internet use, gaming, and television viewing) among children. If the target population was described as “adolescents,” “teenagers,” “school-aged children,” or “students,” the record was excluded without reading the abstract. Studies of older children, adolescents, or young adults who assessed their DT use in early childhood retroactively were excluded. If the title mentioned the term “review” or “meta-analysis,” the study was excluded from our selection. If we discovered that a certain record does not refer to a peer-reviewed paper during the screening process, it was excluded from our selection. Titles referring to using DT for educational or therapeutic purposes were excluded from the selection. No automation tools were used for screening.

During the full-text review, studies on children outside the specified age range were excluded. Studies with mixed age samples were retained if measures for the target population were present, although outcomes and risk factor correlations were not reported, as they may not necessarily apply to children aged <6 years. Records were excluded if they used questionnaires that were not fully accessible; focused solely on screen time, devices, or content type; lacked key information; or were not in the English language.

The first version of the data charting form, that is, its items and response categories for each item, was developed based on the study objective and was agreed upon by all authors. This version was pilot-tested by attempting to fill in the data for the first 20 full-text records on our list. On the basis of our findings, we made no changes to data items. However, we did adapt or add certain response categories for each item. The data charting was performed with the Excel (Microsoft Corp) software. Two researchers independently reviewed each eligible record and extracted data according to the previously established response categories in the charting form. Any inconsistencies regarding record eligibility or minor discrepancies in reported findings were identified and resolved on a case-by-case basis through discussions among the authors. While formal interrater reliability testing (eg, Cohen κ) was not conducted, we ensured consistency through regular meetings to discuss and resolve discrepancies, thereby maintaining a high level of reliability throughout the data extraction process.

The data from each eligible record, available in full text, were extracted according to the following items:

The evidence is presented in a table format, in 3 tables. Multimedia Appendix 1 [26-119] lists all papers included in the final selection and summarizes their key characteristics (eg, year of publishing, sample characteristics, and country) and the measures of PDTU that were used. Due to conceptual similarities among many single-item PDTU measures, we grouped them into categories (eg, age of first smartphone use, age of first television use, and use of DT before 1 year of age were classified as measures of early exposure).

The process of identifying papers that meet the eligibility criteria is shown in Figure 1.

For each of the 95 identified papers, certain characteristics were extracted and summarized in a table format (Multimedia Appendix 1). In most (n=85, 89%) studies, PDTU measures were intended for preschool children. A total of 40 (42%) studies also considered toddlers as their target group, while only 7 (7%) studies included infants. A large majority (n=86, 91%) of studies were conducted with children with no particular specifics or deficits. Most (73/95, 77%) of the conducted studies could be described as cross-sectional, while only 6 (6%) were longitudinal. In addition, 6 (6%) studies used an experimental research design and a further 10 (10%) studies described questionnaire development. The findings of all longitudinal and experimental studies were discussed separately to assess the causal relationships of PDTU measures to relevant outcomes.

Our scoping review showed that there are many patterns of children’s interaction with DTs beyond quantity of use, which can be seen as problematic in terms of their potential for negative consequences for children. It seems that PDTU should be understood as a multifaceted construct containing much more than excessiveness of use. A crucial observation we made during our review is the distinction between conceptualizing PDTU as a group of risky behaviors (ie, various ways of using DTs), which are likely to lead to negative outcomes, or as a group of symptoms of a presumed underlying condition (ie, addiction to DT). Existing composite measures for PDTU (ie, scales and questionnaires) have represented both conceptualizations, with the symptom view being more common. However, when proposing symptoms of a new disorder, the primary information source should, in our view, be clinical observations of multiple experienced mental health professionals working with young children. Instead, items of the reviewed PDTU instruments have mostly been generated based on reviewing the literature, commonly from established behavioral addictions in adolescents or adults, or through adapting established instruments intended for older children. In some cases, clinicians were later consulted to propose any necessary changes to items.

The PMUM-SF was the most commonly used instrument in empirical research and consists of various “symptoms” of problematic use in line with other reviews [120]. It was shown to be adequately reliable and correlated with various PDTU measures, while there is also some evidence regarding its structural validity and ability to predict relevant outcomes. However, some arguments against its validity can be made. First, its content is based on the Diagnostic and Statistical Manual of Mental Disorders–fifth edition criteria for internet gaming disorder [121], for which there is a lack of expert consensus [122]; in fact, several of them (eg, tolerance, withdrawal, and deceiving others) were later discarded from the International Classification of Diseases–11th edition definition of gaming disorder [123]. Second, the concept of PDTU extends beyond the realm of gaming and is, therefore, likely to manifest differently. Third, the criteria for internet gaming disorder were proposed for the adult or adolescent population and should not be expected to function well for the population of preschool children. Finally, Problematic Media Use Measure was originally validated on a sample of children aged 4 to 11 years, or even up to 14 years, for which significant diversity of PDTU can be expected. Unsurprisingly, some of its factors seem inappropriate for preschool children (eg, “jeopardized or lost a relationship or had compromised functioning in school due to use” and “continued use despite psychosocial problems”). Looking at the other 17 reviewed measures, both comprehensiveness and justifications for their proposed content or factor structure, as well as the presented evidence regarding the instruments’ validity, leave much to be desired. In our view, current evidence does not yet point toward a single comprehensive, reliable, and valid measurement tool for any of the 2 PDTU conceptualizations we observed in infants, toddlers, or preschool children.

Remaining consistent with our proposed definition of PDTU as any pattern of DT use that interferes with children’s functioning, we argue for defining PDTU through a collection of risky behaviors. This approach offers several benefits. First, focusing research efforts on developing, measuring, testing, and refining the PDTU concept in this way would yield valuable insights into the most significant ways children use DTs to their detriment. From a public health perspective, this focus has great potential to aid prevention efforts aimed at reducing the incidence of PDTU in children and the harm it causes. With high-quality evidence about the risks associated with specific DT practices, the effectiveness of awareness campaigns among parents and the screening of children for risky behaviors could be greatly improved. In contrast, adopting the addiction view of PDTU would do little to identify preventable DT practices causing harm, while screening for “addiction” symptoms would likely identify children with significant impairments in functioning, which is a notably delayed point from a prevention standpoint.

The findings of this review provide valuable insights into the concept of PDTU and how it should be measured and can thus serve a wide range of stakeholders, such as researchers, public mental health professionals, clinicians, educational professionals, policy makers, and others. The highlighted shortcomings of existing PDTU measures indicate the need for comprehensive, evidence-based, and standardized tools to assess early PDTU. The lack of such a tool challenges comparisons across studies and limits the development of evidence-based interventions, which has also been emphasized by other researchers [23,120]. Therefore, the results of our study can serve researchers as a basis for the development of age-appropriate measurement tools, that is, tools targeting preschool children specifically, instead of adapting measurement tools intended for adolescents or adults. Moreover, the key criteria that these tools should follow are to measure PDTU as a group of risky behaviors rather than addiction symptoms since the former provides more benefits regarding identifying and mitigating harm. Furthermore, these findings can serve as a foundation for designing informed longitudinal studies to identify causal relationships among DT use behaviors and related long-term outcomes and to better monitor PDTU in the most susceptible populations, that is, infants, toddlers, and preschool children.

Furthermore, the results of this study can serve researchers and clinicians collaborating to develop assessment tools that ensure that symptoms and behaviors reflect clinical realities. The findings can enhance screening practices and inform clinicians on how to effectively include PDTU screening in routine developmental assessments to support early identification of potentially risky behaviors (eg, bedtime use, solitary use, or the use of DT for emotional regulation). Early identification and intervention can mitigate potential negative outcomes, such as developmental delays and mental health problems. In terms of policy and public health implications, the findings of the review can inform policy makers to support and promote the establishment, implementation, and advocacy of guidelines on DT use and the development and establishment of policies promoting healthy digital habits, especially for at-risk children and families. Meanwhile, public mental health specialists can use these results to design and implement targeted public health interventions, such as awareness campaigns and programs aimed at educating families about the potential risks associated with specific DT use practices.

A key limitation of the findings resulting from our scoping review is the relative absence of firm evidence regarding the effects of any patterns of PDTU and certain undesirable outcomes. On the one hand, experimental and longitudinal research in this area is scarce, which means the conclusions are mainly based on correlational data from cross-sectional studies. On the other hand, even cross-sectional studies including PDTU measures beyond exposure are far from numerous for this population. Due to this, despite our recognition of the need to differentiate between findings and recommendations for infants, toddlers, and preschool children, we are currently unable to provide separate conclusions for each of these subgroups. In addition, due to our decision to only study measures of PDTU in children and due to most of these measures not including direct observation of behavior, a somewhat arbitrary decision had to be made regarding how indirectly a certain measure should target children’s behavior to still be considered a measure of PDTU. We expect that only a considerable amount of high-quality psychometric analyses will eventually reveal ways in which PDTU can be measured and how it cannot be. Furthermore, our scoping review did not include a search of gray literature, as we expected that useful findings regarding the negative outcomes of PDTU measures are much more likely to come from peer-reviewed scientific papers, although some measures may have been missed on this account. Finally, as the primary purpose of our scoping review was the identification and description of various PDTU measures, we did not conduct any risk of bias analysis. Still, some of our conclusions partly depend on the extent of evidence regarding each measure, and thus, evaluating the risk of bias in each source of evidence would have been an added benefit.

In times when digital devices are increasingly accessible and used by children from infancy onward, researchers have begun to realize that screen time is likely not the optimal or sufficient way to assess the risk of troubling outcomes due to early device use. Our scoping review showed that many different measures of PDTU in early childhood exist, focusing on much more than mere exposure. While the extent of correlational evidence suggests that many patterns of DT use may be problematic, the number of displayed longitudinal effects on adverse outcomes is still insufficient to establish firm conclusions about their detrimental effects. Nevertheless, based on the findings of reviewed empirical studies, we recommend including the following measures in any assessment of children’s PDTU: early exposure to digital devices, device use before sleep or devices in the bedroom, and cousing devices or its counterpart, solitary device use. Moreover, device use during meals, device use for emotional regulation, device multitasking, and technoference may be promising PDTU measures but would benefit from more research to confirm their predictive potential. Research regarding the effects of other PDTU measures beyond exposure is still relatively modest.

This review shows that a lot of work remains to be done to establish the key problematic patterns of DT use in early childhood and how these patterns should be measured. Using reliable, valid, and comprehensive measures in this area is a prerequisite to fully assess and gain insight into the short- and long-term impact of DTs on children’s overall well-being. We urge researchers to use more quasi-experimental and longitudinal research designs, testing the effects of particular patterns of PDTU on children’s health and well-being while keeping the ethical concerns of these studies in mind.