New generations live with electronic devices and media as a central part of their daily lives.1,2 Today, usage patterns have evolved, and smartphones have become the most widely used devices for digital consumption across all age groups and are now ubiquitous in modern society.3,4 Smartphones provide immediate access to a vast range of applications, content, and services.3–5 Device ownership is occurring at increasingly younger ages, and due to the limited current understanding of the effects of these devices, many parents may not fully grasp the potential repercussions of their children’s use.3,4 Thus, the features of these devices and their widespread acceptance by families have contributed to a rise in screen time in the pediatric population worldwide.3,4 Limited parental supervision, combined with exposure to inappropriate or potentially harmful content—sometimes influenced by specific digital platforms—can increase the risks associated with smartphone use and contribute to an unsafe environment for children and adolescents.7

It is difficult to find a balance in this area, although it all depends on the variables and populations of interest, and it is an active research topic and a subject of considerable public and scientific debate.1,3,5,8 There is controversy about the possible effects and patterns of screen use in children and adolescents.8,9 Although some beneficial effects of interactive screen time have been identified, excessive use has been associated with negative impacts on the physical, behavioral, and cognitive development of young people.10 Excessive screen time may interfere with a child’s learning opportunities and overall development, potentially emerging as a new determinant of health that warrants further investigation in the pediatric population.11

Many children and adolescents in developed countries exceed recommended screen time limits, and social media, audiovisual platforms, and games are the contents consumed most frequently, often at the expense of time spent on face-to-face interactions.1,2,6,12 As mobile screen exposure is increasingly seen as an addictive activity, with the pediatric population being particularly vulnerable, organizations such as the Spanish Association of Pediatrics (SAP), the American Academy of Pediatrics (AAP), and the World Health Organization (WHO), among others, have issued reports with recommendations for appropriate global screen time limits.8,9,13 However, it is important to note that most of the scientific evidence on which these recommendations are based concerns television watching.8,9,13

For scientific advances to be relevant to society and applicable to public health policy, the correct assessment of health determinants in relation to screen time is necessary to establish effective surveillance, oversight and evaluation systems to monitor and reduce the impact on the health of the population of possible future addictive behaviors.14 While new measurement trends, such as mobile applications and tracking tools, are emerging, the methodology is still inconsistent and the analysis of screen time continues to be a secondary concern.15

Research in this area is growing; however, to date, no review has been published that all the recent literature on how screen time is measured in cross-sectional studies in children aged less than 18 years. Therefore, we performed a scoping review with the aim of describing the measurement tools used to assess smartphone screen time in children aged less than 18 years in cross-sectional studies.

The reporting in this review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) method.16

We conducted a scoping review to systematically detail the available scientific evidence on the measurement instruments used to assess the variable “smartphone screen time” in children and youth. The following research question was formulated:

“What measurement methods are utilized to assess smartphone screen time among children and adolescents aged less than 18 years?”.

Selection of sources of evidence

RefWorks was used to store information on the selected studies. The title and abstracts of all articles obtained during the initial broad search were reviewed independently by two reviewers (CCL and JMMS) to identify potential eligible studies. Two reviewers (CCL and JMMS) independently extracted and assessed full-text articles that were considered candidates for further analysis based on predefined eligibility criteria.

Two investigators (CCL and JMMS) independently extracted and reported data on the following aspects of each study using standardized forms: study design; year of publication; description of study population; measurement of smartphone screen time; and study outcomes. Any differences of opinion were resolved through group meetings between all reviewers to reach consensus. Fig. 1 shows the flow diagram of the study selection process (adapted from PRISMA).

Figure 1.

The following patches are recommended to bring the diagram closer to the PRISMA format.

Finally, we divided the review in two sections according to the different characteristics of the sources: (1) articles measuring only smartphone screen time (n = 14); (2) articles measuring screen time for smartphones and other devices (n = 75). The variables for which we retrieved data for each of these sections were: (1) Articles measuring only smartphone screen time: first author and year of publication, study objective, study design, measuring instrument, validation of questionnaire, item measuring smartphone usage, answer options, respondent, and main outcome concerning smartphone screen time. (2) Articles measuring screen time for smartphones and other devices: first author and year of publication, study objective, study design, measuring instrument, validation of questionnaire, item measuring screen time for smartphones and other devices, answer options, respondent, types of screen studied and main outcome concerning smartphone screen time (Supplementary Table).

A total of 321 potentially relevant articles were identified. After reading the titles and abstracts and removing duplicates, a total of 146 full text articles were assessed for eligibility; of these, 57 articles were excluded for the following reasons: not original articles (review, non-scientific articles or not in included languages) (n = 31); reporting parental smartphone screen time (n = 8); studying other devices, not measuring smartphone screen time (n = 18) (Fig. 1). Of the 89 included studies, seven used standardized questionnaires, of which only one had been designed for the primary purpose of assessing smartphone screen time.

Table 1 presents the main characteristics of the 89 studies. The target population varied. Most studies included more than one age group (34.8%), and adolescents were the most studied age group (28.1%). The sample size was also heterogeneous. More than a third of the articles (37.1%) were conducted in samples greater than 500. The continent with the most published articles was Asia (40.4%), followed by Europe (34.8%), America (21.4%) and, lastly, Oceania (2.2%). Almost all studies (82%) used self-report questionnaires to assess screen time. The questionnaire was completed by the child in almost half of the articles (48.3%). When it came to the reporting of the screen time variable, more than half of the researchers expressed the results in hours per day (53.9%). The questionnaires used were not validated in 90.1% of the included articles. Only 15.7% of the articles measured smartphone screen time alone, the rest (84.3%) included smartphone and other devices. In addition, 95.5% of the studies did not document the first or last use of the day. Most of the studies were published before 2020 (79.8%).

Table 2 presents a summary of the studies who focused exclusively on smartphone screen time. Most of the articles included in this section measured smartphone screentime by means of self-report questionnaires that had not been validated.17–26

Self-report questionnaires generally directed children or parents to freely report their estimated time of smartphone use in a day or the last week. Only two of them18,19 presented a Likert scale to provide the answer. In all other studies, the answer was given in hours per day.

Two researchers used a self-developed application as a measuring instrument. Einthoven et al.15 did not use a questionnaire, but a monitoring application installed on the teenagers’ smartphones for five weeks. Similarly, Marin Dragu et al.27 used an application installed in the smartphone as a measuring instrument for 30 days. Both applications tracked usage time in the background.

Only two studies, by Olivella-Cirici et al.28 and Al-Amri et al.,29 used validated questionnaires to assess smartphone usage time. The primary purpose of both instruments, the Mobile-Related Experiences Questionnaire (CERM), in Spanish language,30 and the Smartphone Addiction Scale-Short Version,31 is to assess for smartphone addiction.

With the exception of the studies by Park and Park,19 Poujoul et al.,20 and Shah and Phadke,26 it was the children who completed the questionnaires. In the studies by Olivella-Cirici et al.19 and Shah and Phadke,26 the questionnaires were completed by the parents, whereas Poujoul et al20 collected responses from both children and parents.

In addition, Olivella-Cirici et al.28 and Goel et al.22 described a prevalence of smartphone usage at bedtime of 70%–80% and 90%, respectively.

On the other hand, the main objective of most of the articles was to assess the association of smartphone screen time with another variable, frequently obesity, sleep or mental health. Only the study by Shah et al.26 focused on the measurement of smartphone screen time. Specifically, it analyzed the age at acquisition of the first phone, daily frequency and duration of mobile phone use, and primary purpose of use (educational, entertainment, or communication). The study also assessed parental perceptions of the appropriate age for introducing the device attitudes toward the child’s use. The statistical analysis was performed using the χ2 and Fisher exact tests, and we defined statistical significance as P < .05.

Our review, based on the available evidence, shows that most children and adolescents living in developed countries use screens for more than 2 h a day. Organizations such as the WHO, the AAP and the SAP have defined screen time at early ages as using these devices for more than 2 h a day. Still, the studies that support these recommendations are outdated, as most of them focused on television watching, without taking into account the use of multiple screens or the rise of the smartphone.8,9,13 In addition, because the range of devices is increasing, as is the purpose and duration of their use, an accurate assessment of screen time would have to include not only time, but also measures of quality of use, content and context.

In relation to this, almost 30% of the reviewed literature studied different age groups without segregation. The needs, content and duration of screen time should not be the same in preschool age as in adolescence, for example. The fact that researchers are beginning to include this variable as a determinant of health brings us closer to the existing problem, although the reported data are not very accurate due to the inadequate monitoring of screen time.

Despite the rise of the smartphone and the concern it is creating within the scientific community, although they try to include this variable as a determinant of health, almost a third of the available studies did not seek to measure the prevalence of smartphone use, but investigated it as a secondary, associated variable. It is not treated as an emerging and key determinant of health in our young. Only a minority of authors18,19,26 focused their research specifically on this objective, and even they rarely used validated measurement instruments. Of the 89 studies reviewed, only 7 employed standardized questionnaires to assess smartphone screen time, and in 6 of these cases, the primary aim was not to directly measure screen time but rather to evaluate broader aspects such as addiction, lifestyle habits or sedentary behavior. This highlights the scarcity of validated tools specifically designed for measuring smartphone screen time and the urgent need for their development in future research. Moreover, very few studies have examined the type of activity or content to which screen time is devoted. The use of current contents or features to which screen time is devoted is studied by few authors. Following the rise of social networks in recent years, some authors have included it in their work (WhatsApp, Snapchat, Instagram…) although with a vague and imprecise approach.18,23

Similarly, some authors are beginning to innovate in screen time measurement tools by installing applications on the smartphone itself and act in the background, tracking the activity.15,27 However, this measurement option does not take into account multiscreen use and is limited exclusively to the monitoring of the selected device.

Other works on the subject try to find sociodemographic characteristics that influence the increase in excessive smartphone use time. Rodrigues et al61,108 found that a low level of parental communication was associated with an increased probability of excessive screen time. Likewise, Olivella et al.28 and Song et al.18 reported a higher screen time in girls than in boys. In developing a measurement instrument, it would be interesting to take these sociodemographic factors into account and to focus on these target populations.

At the legislative level, some countries are beginning to take measures in the school setting by regulating the use of smartphones through internal policies.29 European countries such as Spain, France and the Netherlands have had internal rules in place for years. Currently, the responsibility lies with the school board, and most schools prohibit the use of phones in the school setting and establish penalties for adolescents.109 In Asia, the Chinese government has officially proposed limiting the use of cell phones by minors. The proposal advocates a “minor mode” in the manufacture of cell phones that will limit the time of use according to the age of the minor.30 In the United States, there is legislation that regulates the use of mobile telephones in the school setting. Under the Technology in Public Schools K-12 Act (CS/HB 379), which became effective July 1, 2023, section 1006.07(2)(f) of the Florida Statutes now states that “a student may not use a wireless telephone communication device during instructional time”.31 Awareness of the issue has gone further in the United States, with nearly one-third of the states suing Meta Platforms, claiming that their social networks Instagram and Facebook are addictive and harmful to children and adolescents and their use is associated with depression, anxiety and insomnia and interferes with education and daily life.32

However, it is difficult to establish appropriate health policies when the monitored health determinant, in this case, excessive smartphone use, is not measured effectively. The wide range of measures used and the limited agreement between the assessments themselves create a scientific gap on the correct measurement of screen time. In this regard, data on screen use, especially smartphones, available for Europe (national health surveys, Eurobarometer, etc) and the rest of the world do not allow for comprehensive surveillance because they do not differentiate between the type of device used (smartphone, computer, console, TV, etc.) and do not provide information on relevant aspects of use that could determine possible addiction in the future.

The main limitation of our review is that it does not include longitudinal studies. We only included cross-sectional studies with greater external validity that would allow extrapolation of the results to the target population. Although longitudinal studies on the impact of screens on the health of the pediatric population include questionnaires to assess screen use, including the use of mobile phones, these questionnaires are not aimed at extrapolating the pattern of use in the pediatric population (external validity), which was the objective of our review.

It is important to note that the source of information used can introduce bias: children tend to underestimate their screen time due to social desirability, recall issues, or, in the case of younger children, difficulties understanding the questions, whereas parents may overestimate it due to not accurately knowing their children’s behaviors. These limitations highlight the need for future research to include validated questionnaires and to focus on the development of standardized and validated tools for this purpose.

Another limitation is the heterogeneity of the studies included, which makes it difficult to synthesize the results. Although our initial intention was to perform a meta-analysis of the studies, this was not possible due to the heterogeneity of the data. In addition, the variation in the terminology used by the authors and the lack of consensus on the definition of screen time made the work difficult. Nevertheless, we were able to identify many common conclusions among the included studies.

This scoping review highlights the scientific gap in the measurement of smartphone screen time in the pediatric population. For public health policies to be applicable and relevant, the use of validated methodology is of the essence. Bani-Issa et al.,33 who used an appropriate instrument, were the authors that reported the highest usage time (up to 7 h/day), consistent with the current boom and lack of control. For usage patterns to be applicable to today’s society, it is especially important to create a measurement instrument that standardizes measurement and, therefore, the results of smartphone screen time in the pediatric population. In this way, existing problems will be correctly identified, allowing development of appropriate usage recommendations and guidelines.

Not applicable.

This study was funded by the “Ministerio de Ciencia e Innovación” of the Government of Spain (ref.: PID2021-122272OB-I00) and by FEDER funds/European Regional Development Fund (ERDF) –a way to build Europe. The Group of Evaluation of Health Determinants and Health Policies of Universidad de Extremadura received support of Junta de Extremadura [grant number CTS063].