IntroductionBackground

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 [], 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 [].

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 [], 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 [], Canadian guidelines [], and Indian guidelines []), 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 [] 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 [-]; cognitive development [,]; psychosocial health []; and sleep duration []. 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 []. 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 [-].

Owing to the shortcomings of screen time, the concept of problematic media use, defined as “...excessive use that interferes with the child’s functioning” [], has gained momentum in the scientific community (eg, [-]). The focus on impairments in functioning is crucial to differentiate normal variation from a pathological level of behavior []. 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 [], 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 [] 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 [] 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 [] 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.

Objectives

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.

MethodsProtocol and Registration

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

Eligibility Criteria

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 []).

Information Sources

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 Search Strategy

The final search strategy consisted of 4 groups of keywords, separated by the Boolean operator AND (). 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.

Table 1. The full search strategy used to obtain relevant records.ConceptKeywordsMeasurescale OR questionnaire OR tool OR inventory OR measure OR instrumentProblematicproblem* OR excessive OR patholog* OR overus* OR addict* OR compulsive OR dependen*Digital technology use“screen us*” OR “screen exposure” OR “screen viewing” OR “screen watching” OR “screen behavio*” OR “media us*” OR “media exposure” OR “media viewing” OR “media watching” OR “media behavio*” OR “digital us*” OR “digital exposure” OR “digital play*” OR “digital behavio*” OR “device us*” OR “device exposure” OR “smartphone us*” OR “smartphone behavio*” OR “smart phone us*” OR “computer us*” OR “computer exposure” OR “computer viewing” OR “computer watching” OR “computer play*” OR “computer behavio*” OR “tablet us*” OR “tablet play*” OR “laptop us*” OR “TV us*” OR “TV exposure” OR “TV viewing” OR “TV watching” OR “TV behavio*” OR “television us*” OR “television exposure” OR “television viewing” OR “television watching” OR “internet us*” OR “internet exposure” OR “internet behavio*” OR “video game us*” OR “videogame play*” OR “game us*” OR “game exposure” OR “game play*” OR “game behavio*” OR “gaming”Young childrenchild* OR infant* OR toddler* OR “pre-school*” OR preschool* OR kindergarten*

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.

Selection of Sources of Evidence

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.

Data Charting Process

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.

Data Items

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

Year of publishingCountries where data collection took placeDevelopmental period: infants (ie, aged 0-1 year), toddlers (ie, aged 1-3 years), preschoolers (ie, aged 3-6 years), school-aged children (ie, aged 6-11 years), and adolescents (ie, aged >11 years)Population: the specifics of the population, other than age, for example, general population, children with attention-deficit/hyperactivity disorder, and children with dyslexiaSample sizeStudy type: cross-sectional, longitudinal, quasi-experimental, and questionnaire developmentFormat of instrument: survey, diary, observation, and interviewMeasures of PDTU: for example, use before sleep and early exposureRisk factors: demographic or population groups with more riskAdverse outcomes and correlates: outcomes associated with a certain aspect of children’s DT use. Only statistically significant findings are listed.Psychometric properties: reliability and any indicators of validity. Positive correlations with a separate PDTU measure (or screen time) serve as an indication of validity.Synthesis of Results

The evidence is presented in a table format, in 3 tables. [-] 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).

ResultsSelection of Sources of Evidence

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

‎Figure 1. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart describing the process of selection of studies. N/A: not available. Study Characteristics

For each of the 95 identified papers, certain characteristics were extracted and summarized in a table format (). 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.

Characteristics of PDTU MeasuresOverview

In the 95 identified papers, a variety of aspects of PDTU were measured. lists 23 distinct categories of PDTU measures found in the selected papers. It presents key characteristics for each measure for PDTU (eg, description and format), as well as all correlations with various risk factors and outcomes found in the papers.

Table 2. Existing measures for problematic digital technology use (PDTU) in children aged 0 to 6 years.MeasureDescriptionPapers (N=95), n (%)FormatDevelopmental periodRisk factorsAdverse outcomes and correlatesCorrelation with other measuresDevices in the bedroomThe presence of digital devices in the room where the child sleeps13 (14)SurveyInfants, toddlers, and preschool childrenFamily income (–)a []
Maternal education (–) []
Poor sleep quality (–), sleep problems, and emotional-behavioral difficulties []
Obesity []
Screen time []
Television viewing time []
Early exposureAge at first exposure to digital screens or screen time before being aged 1 or 2 y24 (25)SurveyInfants, toddlers, and preschool childrenFamily income []
Child’s age (–) [,,]
Maternal education (–) []
Parental education []
Autistic behavior []
Autistic spectrum disorder []
Traumatic experience []
Family harmony (–) and parental anxiety or stress []
Poor sleep quality (–) []
Sleep problems [,]
Emotional-behavioral difficulties []
Astigmatism risk []
Cognitive developmentb (–) []
Feeding problems and anger []
Myopia []
Social development (–) []
Hyperactivity [,]
Psychosomatic problems and psychological health (–) []
Problematic use []
Screen time [,,]
Gaming []
Use during mealsUse of digital screens during mealtime12 (13)SurveyInfants, toddlers, and preschool childrenWeight status []
Difficult temperament []
Motor development (–) []
Feeding difficulties and time spent eating []
Screen accessibility []
Screen time []
Use before sleepFrequency of digital device use before going to bed, typically within 1 h before bedtime9 (9)Survey and diaryInfants, toddlers, and preschool childrenFamily income (–) []
Household chaos []
Self-regulation ability (–) []
Late sleep timing, sleep problems, sleep duration (–), and sleep variability []
Motor development (–) []
Restrictive mediation (–), instructive mediation, and couse []
Device multitaskingExposure to ≥2 digital screen media simultaneously2 (2)Survey and interviewInfants, toddlers, and preschool childrenMaternal education (–), paternal education (–), and positive parenting (–) []
Behavioral problems []
Preschool cognitive ability (–) []
Restricted useParent’s use of rules and restrictions regarding the child’s use of digital media and whether the child obeys (also called restrictive mediation)22 (23)Survey and interviewInfants, toddlers, and preschool childrenBehavioral problems []
Executive functioning (–) []
Gaming []
Problematic use (–) [,]
Background exposureAmount of exposure to digital devices turned on in the background, while the child is occupied with other activities12 (13)Survey and observationInfants, toddlers, and preschool childrenMaternal education (–) []
Ability to delay gratification (–) and difficult temperament []
Parental television time []
Screen time [,]
Problematic useVarious composite measures of problematic use of digital devices or technologies, including additional measures27 (28)SurveyToddlers and preschool childrenMale individual [,,]
Family income (–) [,,]
Unmarried [,]
Non-White individuals []
Parental age (–) [,]
Parental education (–) [,,,]
Nonworking mother [,]
Single parent, extended family, family size, rural setting, day care use (–), and siblings []
Age [,]
Cognitive stimulation at home (–) []
Parental efficacy (–) []
Parental screen use and parental anxiety []
Maternal stress []
Expressive vocabulary (–) [,]
Phonological processing (–) [,]
Emerging literacy (–) [,]
Structural brain deficits in areas supporting language []
Negative affect and effortful control (–) []
Delaying essential needs []
Behavioral problems and emotional intelligence (–) []
Physical conflict []
Parent-child relationship quality (–) []
Early exposure []
Instrumental use []
Emotional regulation [,] screen time [,,]
Television or video watching []
Inconsistent mediation and restrictive mediation []
Screen time in one sittingAmount of time on digital devices that the child spends in one sitting2 (2)SurveyToddlers and preschool childrenDelaying needsDelaying daily needs during device use2 (2)SurveyToddlers and preschool childrenEducational useParents providing digital devices to their children to educate them7 (7)SurveyToddlers and preschool childrenUse for entertainmentParents providing digital devices to their children to entertain them5 (5)SurveyToddlers and preschool childrenEmotional regulationParents providing digital devices to their children to improve their mood or calm them down12 (13)SurveyToddlers and preschool childrenParental education (–) [,]
Male individuals and temperamental surgency []
Emotional difficulties andexecutive functioning (–) []
Problematic use [,]
Emotional response []
Screen time []
Instrumental useParents providing digital devices to their children to complete chores and tasks more easily and to distract them, using devices as a “babysitter”11 (12)SurveyToddlers and preschool childrenInstructed useFrequency of parents helping children understand the digital content through instructions and explanations during digital device use (also called instructive mediation)7 (7)SurveyToddlers and preschool childrenAge (–), male individuals (–), maternal education, and positive parenting []
Screen time and use before sleep []
CouseThe extent to which digital devices are used together with caregivers or siblings, as opposed to solitary use, sometimes as a ratio compared to total screen time20 (21)Survey and diaryToddlers and preschool childrenLanguage development delay (–) []
Receptive language and expressive language [,]
Emotional liability (–) []
Social development []
Use before sleep []
Screen time (–) [,,]
Perceived negative effectsParents’ perceived effect of child’s device use on their hobbies, concentration, social isolation, vision, hearing, appetite, sleeping, and family time3 (3)Survey and interviewToddlers and preschool childrenEmotional reactivityFrequency or intensity of child’s negative emotions as a response to devices being taken away or their use being limited2 (2)Survey and observationToddlers and preschool childrenEmotional regulation and problematic use []
Self-regulationChild’s lack of ability to disengage from activities on digital devices1 (1)SurveyPreschool childrenSensory regulationUsing screen media to help with sensory regulation by taking in or blocking out sensory input1 (1)SurveyPreschool childrenTechnoferenceFrequency of interruptions or interferences in parent-child interactions due to child’s or parents’ use of digital devices2 (2)SurveyPreschool childrenBehavioral problems [,]
Psychosocial difficulties and frequency of parent-child interaction (–) []
Prosociality (–) []
Screen time []
Parents’ problematic use [,]
Conflict due to useConflict between parent and child because of or related to child’s device use1 (1)SurveyPreschool childrenConcerns about useFrequency of parent concerns regarding child’s digital technology use2 (2)Survey and interviewPreschool children

aThe negative sign indicates a negative correlation between a risk factor or outcome and PDTU measure.

bLongitudinal associations are italicized.

cData not available.

Of 95 studies, 29 (30%) used a composite measure of PDTU (ie, developed psychometric instruments and labeled problematic use), which contained multiple PDTU aspects within a single measurement tool. The most common among single-item measures used was early exposure (n=24, 25%), followed by restricted use (n=22, 23%) and couse (n=20, 21%).

In terms of measurement format, survey-based measures of PDTU were by far the most common. Each of the listed PDTU measures existed in survey format in at least 1 study. In total, 34% (8/23) of the PDTU measures used a nonsurvey format in at least 1 study. The data for 17% (4/23) of the measures were obtained through an interview, 9% (2/23) through a diary format, and 9% (2/23) through observation. For each PDTU measure, data were obtained on preschool children (aged 3 to 6 years) in at least 1 study. A large proportion (16/23, 78%) of measures was also applied to toddlers (aged 1 to 3 years). Less than a third (7/23, 30%) of all measures were used in studies, which included infants (aged 0 to 1 year).

Risk Factors

The most commonly reported demographic risk factor for PDTU was lower parental education (ie, either maternal or paternal). Of the 23 PDTU measures, negative associations with parental education were found for 7 (30%) measures or 70% (n=16) of all measures for which any risk factors were reported. In addition, being a male participant was found to be a risk factor for 3 (13%) measures and having autism spectrum was found to be a risk factor for 2 (9%) measures. The child’s age was a risk factor for 3 (13%) PDTU measures, although both lower and higher age were found to be risk factors, depending on the particular aspect ().

Detrimental Outcomes

PDTU measures were associated with 28 unique, undesirable outcomes. Of 23 measures, 11 (48%) were found to be associated with behavioral-emotional difficulties of children, while 7 (30%) were correlated with developmental outcomes (eg, deficiencies in language, cognition, or motor development). A total of 6 (26%) measures were associated with undesirable habits (eg, poor sleeping and eating habits or delaying needs), and another 3 (13%) measures were associated with physical outcomes (eg, obesity and vision problems).

Findings From Longitudinal Studies

A longitudinal study by Supanitayanon et al [] showed that delayed introduction to DTs (a measure of early exposure) and verbal interaction during media use in the first 2 years of life (ie, a measure of instructive mediation) significantly predicted a child’s cognitive development at 2, 3, and 4 years of age. A longitudinal study by Srisinghasongkram et al [] showed that screen media multitasking at 18 months (ie, device multitasking) is associated with decreased preschool cognition at 4 years and behavioral problems at 4 and 6 years. In a longitudinal study by Radesky et al [], bidirectional cross-lagged correlations between using devices for calming purposes and emotional reactivity (ie, instability) were found, specifically in boys and children with higher temperamental surgency. A study by Coyne et al [] showed a longitudinal association between 2 PDTU measures: restricted use was associated with lower problematic use. A study by Gueron-Sela et al [] showed no longitudinal relationship among screen time, background exposure to DTs or using DTs for emotional regulation during lockdown periods, and children’s behavioral problems after lockdown.

Instrument CharacteristicsOverview

Among the measures of PDTU, we identified 18 multi-item measures of problematic use, which were either fully available or had their items described in sufficient detail. The most commonly used was Problematic Media Use Measure–Short Form (PMUM-SF), used in 9% (9/95) of the studies. All other instruments were used in 1 or 2 studies at most. All the identified instruments were applied to preschool children (aged 3-6 years) in at least 1 study. Only 22% (4/18) of them were also tested on toddlers (aged 1-3 years), while no instrument was used in studies on infants (aged 0-1 year). summarizes important characteristics (eg, theoretical background and psychometric properties) of all measurement tools targeting PDTU.

Table 3. Characteristics of existing composite measures for problematic digital technology use (N=18).QuestionnaireDescriptionFactors or content categoriesItems, nBackgroundYearReferencesReliabilityValidityDevelopmental periodTechnology addiction scaleA parent report measure of technology addiction for children aged 2 to 5 yImpulsiveness (impulsiveness symptoms of using a technological device)
Implicit attitudes (emotional symptoms and reactions toward the use of a technological device)
9Item pool was generated based on internet addiction symptoms (in adolescence)2023[]Cronbach α=0.90CFAa: CMINb (df)=2.141, GFIc=0.964, CFId=0.981, and RMSEAe=0.061Toddlers and preschool childrenDSEQf for young childrenA parent report measure of screen exposure for children aged 2 to 5 ySociodemographic screen time exposure and home media environment
Level of physical activity
Media-related behaviors and parental perceptions domain
86Questionnaire was developed based on existing tools, parent interviews, and expert interviews2021[]Cronbach α for each subdimension were 0.82 and 0.74. κ value=0.52-1.0 and ICCg=0.62-0.99Good face and content validity as judged by 9 independent expertsToddlers and preschool childrenSeven-in-Seven Screen Exposure QuestionnaireA parent report measure of problematic screen exposureScreen time
Early exposure
Use during meals
Use before sleep
Content
Coviewing
Restrictive mediation
7Items were designed using the AAPh recommendations for children’s media use2021[]Cronbach α=0.49Use of touchscreens (+)i and EFAj found 3 factorsToddlers and preschool childrenElectronic Media Use QuestionnaireA parent report measure of how “serious” the electronic media use of the child isElectronic media time management
Interpersonal and health conditions caused by electronic media use
Life conflicts arising from electronic media use
Emotional experiences related to electronic media use
14Questionnaire adapted from the Video Game Use Questionnaire by changing the term “video game” to “electronic media” and reducing item numbers based on factor analysisk2023[]Cronbach α=0.93, Cronbach α of each subdimension were 0.73, 0.80, 0.77, and 0.82CFA: χ2=2.71, RMSEA=0.08, GFI=0.91, NFIl=0.91, IFIm=0.94, TFIn=0.92, and CFI=0.94Toddlers and preschool and school-aged childrenPMUMoA parent report measure of child’s addictive use of screen mediaPreoccupation
Withdrawal
Tolerance
Unsuccessful attempts by parents to control use
Loss of interest in previous hobbies and entertainment
Deceived others about use
Use to escape or relieve a negative mood
Jeopardized/lost a relationship or had compromised functioning in school due to use
Continued use despite psychosocial problems
27Items were generated based on criteria suggested for IGDp in the DSM-5q. Content used to generate items that correspond to the DSM-5 criteria were drawn from the literature on problematic media use in adolescents, clinical experience, and interviews with mothers of children aged 4 to 8 y.2019[,]Cronbach α=0.97PMUM-SFr (+), screen time (+), concerns about use (+), and instrumental use (+); PMUM predicts psychosocial functioning over and above screen time (24% of additional variance explained)Toddlers and preschool and school-aged childrenPMUM-SFA parent report measure of child’s addictive use of screen media; a short version of PMUMPreoccupation
Withdrawal
Tolerance
Unsuccessful attempts by parents to control use
Loss of interest in previous hobbies and entertainment
Deceived others about use
Use to escape or relieve a negative mood
Jeopardized/lost a relationship or had compromised functioning in school due to use
Continued use despite psychosocial problems
9Items were based on the DSM-5 criteria for internet gaming disorder2019[,,, ,,, -]Cronbach α=0.93, 0.80, 0.94, 0.90, and 0.91PMUM (+), screen time (+), concerns about use (+), parent-child conflict over screen media use (+), emotional regulation (+), parental media efficacy (+), and parental screen addiction (+); PMUM-SF predicts psychosocial functioning over and above screen time; acceptable fit in CFA (RMSEA=0.085; CFI=0.961; SRMRs=0.024); and measurement invariance between boys and girls indicated that factor structure is the same for both groups.tToddlers, preschool and school-aged children, and adolescentsPMPUSuA parent report measure of problematic mobile phone useDeprivation
Adverse outcomes
Control problems
Interaction avoidance
26The original version of the scale was aimed at university students. Items were generated based on interviews/open-ended questions with students. PMPUS was adapted for children through a focus group discussion with experts.2016[]Cronbach α=0.90 (factors from 0.90 to 0.91)Early exposure (–), Instrumental use (+), Emotion regulation (+); EFA found the listed 4 factorsPreschool childrenPCIATwA parent report measure of child’s internet addiction20 (21)The original version of the test was aimed at adolescents. A total of 5 items were removed as they were not relevant for preschool children.2016[]ICC=0.92Panel of experts confirmed content validity (CVI=0.989)Preschool childrenSMALLQyA parent report measure of digital media habits of children, which can be used to monitor changes over timeDigital media environment at home
Parent digital media habits
Child digital media habits (ie, outside of preschool)
Parent perception of digital media use
Parent concerns
Parent awareness of guidelines
“Pon-digital (physical and playing) habits”
25Items were based on reviewed literature, focus group, and cognitive interviews2019[]—Acceptable face and content validity as judged by 4 independent expertsPreschool childrenScreenQ surveyA parent report measure of adherence to AAP recommendations for media use in childhoodAccess to screens
Frequency of use
Content viewed
Coviewing
15The conceptual model for the ScreenQ survey was derived from aspects of media use cited in current AAP recommendations.2020[,]Cronbach α=0.74Criterion-related validity referenced to external standards of child cognitive skills and home cognitive environmentPreschool childrenS-scalez for childrenA parent report measure used for screening of problematic smartphone use in childrenSelf-control failure
Salience
Serious consequences
9The scale was based on the SAPSaa, which was developed based on clinical experiences, research findings, and previous diagnostic instruments.2016[]Cronbach α=0.80Screen time (+), tv/video watching (+)Preschool childrenAddiction measurement tools of measuring smartphone addiction of children and adolescentsA parent report measure of child’s smartphone addiction tendenciesInterference with daily life
Voluntary isolation
Need for compulsory control
Personality distortion
18—2011[]Cronbach α=0.66 to 0.90 for factorsCFA loading levels between 0.59 and 0.80Preschool childrenPTUS-YCabA parent report measure of child’s problematic technology useContinuity of use
Resistance to control
Effect on development
Deprivation escape
26Items were based on reviewed literature and criteria for internet addiction2022[]Cronbach α=0.94 (factors from 0.88 to 0.94)EFA: 4 factors with factor loadings between 0.37 and 0.83. AVE for factors from 0.41 to 0.60. CFA: 4 factor structure – RMSEA=0.076, NFI=0.871, CFI=0.906, IFI=0.907, SRMR=0.071Preschool childrenSAS-SVacA parent report measure of proneness to problematic smartphone useDaily life disturbance
Positive anticipation
Withdrawal
Cyberspace-oriented relationship
Overuse
Tolerance
10SAS (used for adolescents) was adapted to be suitable for young children2013[]Cronbach α=0.91Inconsistent mediation (+), restricted use (–)Preschool childrenQQ-MediaSEEDadA parent report on quantity and quality of digital media use for bilingual children aged 3 to 6 yDemographics
Digital media use
Parental mediation
—Inspired by existing tools2022[]Cronbach α for each subdimension were 0.83, 0.84, 0.90 and 0.84Appropriate face validity as judged by stakeholders. PCAae shows two components “restriction” and “instruction, supervision, and co-use”Preschool childrenYC-CGDafA parent report measure of computer gaming disorder symptoms in young children11Substance-related addiction criteria of ICD-10ag2017[]Cronbach α=0.83Principal component analysis: One component solution, 38.2% variance explained. Acceptable PCA factor loadingsPreschool children, school-aged childrenVideo Game Engagement in Children QuestionnaireA parent report measure of video game engagementInterest in the activity
Focus during play
Challenges in discontinuation
Social disengagement
19Original set of items reduced based on EFA and CFA results2023[,]Cronbach α=0.93, Cronbach α of each subdimension were 0.86, 0.82, 0.80, and 0.86EFA: 4 factors, CFA: CMIN/(df)=4.8, RMSEA=0.07, CFI=0.91, TLIah=0.90, and SRMR=0.058Preschool and school-aged childrenSASC-PaiA parent report measure of a child’s smartphone addictionSmartphone dependence
Psychological ill health
Physical ill health
Academic performance
Social relationship
Family relationship
24Domains of smartphone addiction were proposed based on previous studies detailing the diagnostic criteria for smartphone addiction2021[]Cronbach α=0.97 (0.82-0.91 for domains), test-retest reliability was 0.96 (0.68-0.85 for domains)PCA was used to establish domains. Each domain included items with>0.30 factor loadings. Content validity was examined by an expert panel of 4 psychiatrists and 4 psychologists. A focus group was identified to establish face validity.Preschool and school-aged children and adolescents

aCFA: confirmatory factor analysis.

bCMIN: minimum discrepancy of confirmatory factor analysis.

cGFI: goodness of fit index.

dCFI: comparative fit index.

eRMSEA: root mean square error of approximation.

fDSEQ: Digital Screen Exposure Questionnaire.

gICC: intraclass coefficient.

hAAP: American Academy of Pediatrics.

i(+): positive correlation.

jEFA: exploratory factor analysis.

kQuestionnaire not accessible.

lNFI: normal fit index.

mIFI: incremental fit index.

nTFI: total fit index.

oPMUM: Problematic Media Use Measure.

pIGD: internet gaming disorder.

qDSM-5: Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition).

rPMUM-SF: Problematic Media Use Measure–Short Form.

sSRMR: standardized root mean square residual.

tData regarding the incremental validity, model fit, and measurement invariance of the PMUM-SF and PMUM were gathered on children aged 4 to 11 years and 4 to 14 years.

uPMPUS: Problematic Mobile Phone Use Scale.

vThe negative sign indicates negative correlation.

wPCIAT: parent-child internet addiction test.

xData not available.

ySMALLQ: Surveillance of digital media habits in early childhood questionnaire.

zS-Scale: Smartphone Overdependence Scale.

aaSAPS: Smartphone Addiction Proneness Scale.

abPTUS-YC: Problematic Technology Use Scale for Young Children.

acSAS-SV: Smartphone Addiction Scale-short version.

adQQ-MediaSEED: Quantity and Quality of Media Screens in Early Education and Development.

aePCA: principal component analysis.

afYC-CGD: young children computer gaming disorder.

agICD-10: International Statistical Classification of Diseases, Tenth Revision.

ahTLI: Tucker-Lewis index.

aiSASC-P: Smartphone Addiction Scale-Parent version.

Content, Factors, and Background

Interestingly, of the 18 instruments, 7 (39%) primarily targeted behavioral patterns of children’s DT use and were named “media use” or “exposure” measures [,,,,,,-]. The other 11 (61%) instruments could be said to measure symptoms, or consequences, of a presumed underlying condition, and 7 (39%) of these were self-declared as measures of either “addiction,” “disorder,” “overdependence,” or “problematic use” [,,,,,,,,,,,,-,,,]. Looking at the proposed factors and content categories of the instruments in , there is a great deal of variety: no 2 instruments (except Problematic Media Use Measure, which exists in a longer and shorter form) shared the same set of factors or content categories. Factors ranged from typical behavioral addiction symptoms (eg, preoccupation, tolerance, and continued use despite problems); various consequences of DT use (ie, “physical ill health,” “adverse outcomes,” and “effect on development”); behavioral patterns (ie, frequency of DT use and DT use before sleep); psychological constructs (ie, “cyberspace-oriented relationship,” “personality distortion,” and “implicit attitudes”); characteristics of the environment (ie, “digital media environment at home”); parenta