Adolescents' perspectives on self-regulation and digital media use

Given the harmful consequences of problematic digital media (DM) use on children's cognitive, emotional, and social development, and the highly addictive nature of the digital environment, children's ability to develop self-regulation in this context is critical. While recent research has begun to explore self-regulation in digital settings, we still know very little about the self-regulatory strategies adolescents employ. This study addressed this pressing gap by investigating the self-regulatory strategies that adolescents use to navigate everyday conflicts related to DM use. One hundred fifty-one adolescents (aged 12–18) were asked to answer three open-ended questions about how they deal with conflicts between their desire to use DM for social and recreational purposes and academic and social demands, as well as how they manage negative emotions arising during DM use. We used a mixed-methods design to analyze the responses, combining qualitative analysis using a constant comparative approach with quantitative analysis examining age-related differences in the response distribution. The qualitative analysis revealed five families of self-regulatory strategies: planning and organizing (e.g., distancing), cognitive (e.g., consideration of future consequences), approaching others, regulating negative emotions (e.g., engaging in a pleasant activity), and external regulation (e.g., parents restricting usage time). Planning and organizing was the most frequently described strategy (70%), while external regulation was the least frequently described (7%). Older adolescents relied more frequently on DM and less on others to regulate negative emotions. The study's findings provide a contemporary map of self-regulatory strategies adolescents use to manage DM in their daily lives. The results underscore the centrality of planning and organizing strategies for adolescents' management of DM use. This heavier reliance on planning and organizing strategies may be a consequence of the highly rewarding and enticing characteristics of many DM platforms, which can curtail the efficacy of cognitive, in-the-moment strategies for inhibition. The relatively low reliance on parents for external regulation highlights adolescents' preference for regulating DM independently and underscores the importance of parental availability to support adolescents rather than regulating DM use for them. Finally, the increased reliance on DM to regulate negative emotions calls for further investigation into its long-term implications for emotion regulation.

Adolescents growing up in the 21st century in industrialized societies are immersed in digital media-saturated environments (Lorenz and Kapella, 2020). Digital media (DM) has become a central part of their lives, serving as a platform for entertainment, socialization, education, and play. However, unlike other developmental contexts such as playgrounds, schools, or peer groups, DM is explicitly designed to encourage and maintain high engagement levels, potentially leading to problematic or excessive usage (e.g., Wegmann et al., 2018). Extensive research has indicated that problematic DM use (e.g., preoccupation with media, loss of interest in other activities, social withdrawal, emotional dysregulation, and excessive use despite negative consequences; Domoff et al., 2019) is associated with increased social and emotional dependency on DM that can hinder the development of interpersonal skills, reduce academic engagement, and negatively affect self-regulation (e.g., Lissak, 2018).

Given the potentially harmful consequences of problematic digital media (DM) use on children's cognitive, emotional, and social development and the highly immersive and addictive nature of the digital environment, children's ability to develop self-regulation in this context is critical. While recent research has begun to explore self-regulation in digital settings (Domoff et al., 2024; Howard et al., 2024), we still know very little about the specific self-regulatory strategies adolescents employ, how these strategies emerge and evolve throughout adolescence, and the role parents play in fostering them. This study directly addresses this pressing gap by investigating the self-regulatory strategies that adolescents use to navigate everyday challenges related to DM use. By mapping these strategies, we lay the groundwork for future efforts to understand how self-regulation in the DM context develops and how parents can support this process effectively.

Self-regulation

The term self-regulation is broadly defined as “the ability to flexibly activate, monitor, inhibit, persevere and/or adapt one's behavior, attention, emotions and cognitive strategies in response to direction from internal cues, environmental stimuli and feedback from others, in an attempt to attain personally-relevant goals” (Moilanen, 2007). This broad definition attempts to establish a common language to describe cognitive, emotional, behavioral, and attentional processes applied to manage a discrepancy between a person's desired goals/mental state and their current internal state or contextual demands (Reinecke et al., 2022). The self-regulation construct thus captures the processes of noticing a conflict or gap, activating strategies to address it, and monitoring the implications of those strategies in relation to a person's long- and short-term goals (Eisenberg and Zhou, 2016).

While there is relative consensus on the overarching definition of self-regulation, the taxonomy of mechanisms involved in the self-regulation process, and their manifestation as self-regulation strategies, vary across theoretical orientations, development and contexts (Nigg, 2017; McClelland et al., 2017). As the current study focuses on adolescents' perspectives on self-regulation in the context of DM use, we were interested in the intentional, top-down strategies (i.e., deliberate, conscious attempts to influence; Eisenberg et al., 2024; McClelland et al., 2017) that adolescents apply to manage their social, academic, and emotional goals in the context of daily DM use (Reinecke et al., 2022).

Within the cluster of top-down processes, Nigg (2017), Eisenberg (2017) and Eisenberg et al. (2024) highlighted the role of cognitive processes falling under the umbrella of effortful control and executive functions that enable individuals to regulate attention (e.g., shift, focus, ignore and distractions), process information in relation to memorized instructions or goals (McClelland et al., 2017) and deliberately inhibit automatic, and unwanted responses. Within this frame, Eisenberg (2017) highlighted the role of the ability to plan and organize as an important aspect of the ability to self-regulate both long-term and short-term goals.

Emotion regulation was also described as part of the capacity for self-regulation, as effective management of emotions was viewed as essential for maintaining homeostasis and reducing reactive behavior that may conflict with short- and long-term goals (Nigg, 2017). In his seminal work on emotion regulation, Gross (1998, 2014) focused less on the cognitive mechanisms underlying regulation and more on the temporal continuum of regulatory strategies. Gross described regulation as taking place at different time points of the emotional process involving antecedent-focused strategies occurring before negative emotions arise (e.g., planning where to go), cognitive strategies that modify the perception of negative emotions during their experience (e.g., reframing), and response-focused strategies that involve behaviors aimed at managing emotional responses (e.g., distraction). To a large extent, this taxonomy aligns with prior theoretical attempts by Gioia et al. (2000) to describe self-regulation along behavioral and cognitive lines, and with Eisenberg's focus on planning as an important aspect of deliberate self-regulation. Together, these cognitive, behavioral, and emotional processes can be conceptualized as forms of intrinsic self-regulation, referring to the internal processes through which individuals regulate their own thoughts, emotions, and behaviors across different contexts and over time (Eisenberg and Zhou, 2016).

In addition to intrinsic self-regulation processes, theorists have expanded the concept of regulation to include interpersonal processes, emphasizing reliance on others as an important component of self-regulation (Fitzsimons and Finkel, 2010). The literature uses various terms to describe these interpersonal regulatory processes, conceptualizing them along a continuum ranging from regulation that originates outside the individual to more mutual and collaborative forms of regulation (Barthel et al., 2018). At one end of this continuum is external regulation, in which individuals are regulated by others, often through external prompts or actions that help them adapt to environmental demands or achieve goals (e.g., a parent removing a distracting toy from a child; Cox et al., 2010). Such externally initiated regulation is particularly central in early childhood, when children rely heavily on caregivers' regulatory support. At the other end of the continuum is co-regulation, which involves more reciprocal and intentional interpersonal processes organized around shared emotional experiences or goals. Co-regulation includes deliberate efforts to seek support from others in order to manage, understand, or cope with emotions and challenging situations, such as approaching a parent to share a distressing experience (Gable and Reis, 2010; Volet et al., 2009).

Developmental theorists like Sameroff (2010) argued that while children's capacity for intrinsic self-regulation increases with age, it is also shaped by the continuous availability of external support (e.g., parents) that complements the child's growing ability to self-regulate throughout different developmental contexts and serves as a scaffold until intrinsic self-regulation matures. Other theorists stressed that self-regulation across the lifespan involves the social context within which it takes place (Volet et al., 2009; Barthel et al., 2018). As such, interpersonal processes of regulation, including co-regulation and external regulation, are part of the self-regulation apparatus. Therefore, when evaluating children's ability to self-regulate in different contexts, it is important to consider both the intrinsic ability for self-regulation that is influenced by a child's characteristics (such as effortful control and executive functioning), and the reliance on social support. Moreover, in contexts that challenge intrinsic self-regulation abilities, reliance on others for self-regulation may continue to play a central role.

Self-regulation during adolescence

Studies on the development of self-regulation capacity have described a shift in children's independent ability for self-regulation during the adolescent years (Gestsdottir and Lerner, 2008). Consistent with characterizations of adolescence as a critical period for the development of higher-order cognitive processes (i.e., cortical development; Larsen and Luna, 2018), research shows that adolescents use cognitive self-regulation strategies more frequently than younger children and can switch between cognitive strategies more flexibly (Compas et al., 2017). Adolescents' improved capacity to rely on cognitive operations to process and manage emotions supports their ability to respond more independently in a fashion consistent with their goals. Studies have also shown that adolescents' executive control networks (Huizinga et al., 2006) and other brain regions that play an important role in cognitive control, such as the lateral prefrontal cortex, parietal cortex, and medial prefrontal cortex (Bunge and Wright, 2007), improve during adolescence. This brain development makes it easier for adolescents to delay immediate gratification, which may improve their ability to regulate impulses in accordance with personal goals.

Nonetheless, despite these areas of development, several studies have described adolescence as a sensitive period characterized by increased sensitivity in reward-related brain areas (Cromheeke and Mueller, 2016), sensation and reward seeking (Romer et al., 2010), and a greater need for social belonging (e.g., Noam, 1999). Taken together, despite the development of more sophisticated self-regulatory strategies, the combination of increased reward sensitivity and partial capacity to inhibit and regulate impulses increases the prevalence of risk-taking and addictive behaviors among adolescents (Chein et al., 2011). During this sensitive developmental period, parents continue to play a role in supporting adolescents' regulatory capacities, with evidence suggesting that higher quality parent-adolescent relationship is associated with better self-regulation (Farley and Kim-Spoon, 2014), and that adolescents rely on both peers and parents to regulate negative affect (Do et al., 2025).

Adolescents' self-regulation and DM

Contemporary literature describes DM as a particularly challenging context for adolescents' self-regulation (Domoff et al., 2024). Children using DM devices are exposed to more appealing, manipulative, and persuasive digital content and applications (Mallawaarachchi et al., 2024; Radesky et al., 2022). The highly rewarding and engaging characteristics of many DM applications and interfaces can challenge children's ability to apply self-regulatory strategies effectively or interact with prior self-regulatory challenges and lead to problematic engagement with DM, which can interfere with a child's long-term development and social, emotional, or academic goals (Domoff et al., 2020a).

Recent studies have demonstrated that children have difficulty disengaging from devices (Munzer et al., 2021) and responding appropriately to parental requests when they engage with commercially available digital content (Webb et al., 2024). Other studies have shown that DM use can interfere with children's and adults' reward systems in a manner that reduces their abilities to modulate their use and reinforces addiction-like behaviors (Wegmann et al., 2018). According to Brand et al. (2016), the repeated socially and emotionally gratifying experiences involved in media use can become conditioned with external cues/notifications generated by many applications. This process can form a cue–reactivity automatic response that can manifest in the experience of constant craving to check messages or to engage in use that can be challenging to inhibit or control. Taken together, the personalized, and highly rewarding design of many DM content and interfaces can make DM a challenging context for self-regulation. The challenges involved in regulating one's behaviors in the DM context may be more profound compared to other developmental contexts (Howard et al., 2024). As a result, adolescents may need to employ distinct or context-specific self-regulatory strategies in order to manage their DM use effectively.

The current study

The scientific literature uses different constructs and terms when referring to children's use of DM (Dienlin and Johannes, 2022). Some refer to the type of device used (e.g., smartphones, internet, television, tablets), whereas others focus on the process or content of use (e.g., gaming, social media, gambling, shopping, pornography consumption). However, in contemporary digital environments, these distinctions are increasingly blurred, as many platforms integrate multiple functions (e.g., gaming environments that include social networking features, or social media platforms that incorporate gaming elements). Given that the current study aims to examine children's developing capacity to regulate and navigate the digital world, we adopted a broad definition of DM in order to capture children's habits across developmental stages, gender, and areas of interest. We were concerned that focusing on a specific medium or content would limit our ability to capture a wide range of DM-based activities, introduce potential gender bias (given known differences in boys' and girls' media usage patterns; Twenge and Martin, 2020), and limit our ability to compare usage habits across developmental stages. Accordingly, we define DM in line with the American Academy of Pediatrics' definition, as an umbrella construct encompassing all screen-based technologies used by children, including but not limited to television, gaming consoles, personal computers, smartphones, and tablets (American Academy of Pediatrics, 2016; Adelantado-Renau et al., 2019; Munzer et al., 2026).

Despite growing concerns about problematic DM use among adolescents, we know surprisingly little about how they actively regulate themselves in this complex environment. Thus, in the current study we asked to understand which specific self-regulatory strategies adolescents employ to promote social, academic and emotional goals that the use of DM can interfere with, and how adolescents use their social environment to support these self-regulation processes (Reinecke et al., 2022). Existing self-regulation models offer broad theoretical frameworks, but they were developed outside of the DM context and often fail to capture the real-life challenges adolescents face, the unique characteristics of the DM context, and the specific means adolescents use for self-regulation. Thus, in the current study we asked to achieve a contemporary and detailed understanding of self-regulation strategies applied routinely in the context of DM use, by adopting a bottom-up approach that directly examines adolescents' accounts of managing challenges related to the DM use (Skinner et al., 2003).

In addition to assessing the different strategies, we were interested in exploring potential age -related differences in strategy use. Specifically, following the existing literature, we hypothesized that older adolescents may rely more on intrinsic and cognitive self-regulation strategies (Compas et al., 2017; Gestsdottir and Lerner, 2008; Sanchis-Sanchis et al., 2020; Tetering et al., 2020). We also examined the frequency of strategy use across different contexts (academic, social, and emotional) in order to obtain an estimate of how self-regulation strategies are distributed across different regulatory contexts (Fombouchet et al., 2023).

We assessed adolescents' self-regulatory strategies in the DM context using a set of open-ended questions. We asked adolescents what they do when there is a conflict between their DM use and other social, emotional, and academic goals or demands. We applied a mixed-methods sequential design (Johnson and Onwuegbuzie, 2004) to identify qualitatively what self-regulatory strategies adolescents use, and to evaluate quantitatively which strategies are more prevalent, and how they are distributed across age groups. The mixed methods approach enabled us to capture specific strategies that are unique to the DM context, as well as to learn how adolescents apply these strategies in their daily life (e.g., what they actually do and on which strategies they rely on frequently), thus providing a rich account of self-regulation as it unfolds in contemporary adolescents' daily lives.

Participants

Participants were 151 adolescents in grades 7–11 who study in the Israeli Jewish public school system. Participants in the study ranged in age from 12 to 18 years (M = 14.43 years, SD = 1.34, 51% girls), with 81.4% of the adolescents being 15 or younger. The majority of the adolescents (96%) were born in Israel. Most adolescents (71.6%) received their own mobile phone devices at 9 years old or younger (M = 8.76, SD = 1.88). According to the parents' report, 12.6% of the adolescents were diagnosed with learning difficulties, and 25.2% were diagnosed with ADHD. Information regarding neurodevelopmental diagnoses was based solely on parent report and was not validated using standardized measures or clinical confirmation. This rate is consistent with recent studies conducted in Israel (for example, 18.2%; Shehadeh-Sheeny and Baron-Epel, 2023). Most parents (86%) were married or cohabiting with their partners and had more than 12 years of education (84.5%). All families identified as Jewish Israelis. Sixty-five percent of parents identified as secular, and 63.5% of the families earned at least the average income (The Israeli Central Bureau of Statistics, 2023). We recruited only children studying in the Jewish public education system due to the large variance in media usage patterns among ethnic and religious groups in Israel (Addi-Raccah and Seeberger Tamir, 2022). All participants received shopping vouchers as compensation for their participation in the study.

Procedure

This study was part of a larger project that examines how children develop the ability to regulate DM during adolescence. Families participating in the study were contacted once a year by the research team via phone call or email, and parents and children were asked to complete online questionnaires pertaining to DM use. For the current study, data was drawn from a single measurement wave conducted in May 2023. This wave was selected to avoid the influence of major external events present in the preceding and subsequent waves (COVID-19 and the Israel–Hamas war). In addition to the annual questionnaires, adolescents were invited to complete three open-ended questions regarding their DM use. The survey was administered online and distributed via an email link. Both parents and adolescents signed consent forms before taking the survey. Parents were instructed to allow their children to complete the survey privately and preferably on the children's own media devices. The study was approved by the ethics committee of the Hebrew University of Jerusalem #28052023.

Measures

Self-regulation strategies in the context of DM use

DM self-regulation strategies were assessed using three open-ended questions, which adolescents answered in writing via the Qualtrics online survey platform. The three domains (academic functioning, social face-to-face interactions, and emotion regulation) were selected based on existing literature linking problematic or dysregulated DM use to academic difficulties, disruptions in social relationships, and emotional dysregulation (e.g., Domoff et al., 2020b; Gioia et al., 2021; Kim, 2017), suggesting that these domains represent key contexts in which DM related self-regulation challenges are likely to emerge. The wording of the questions was designed to capture a broad range of strategies that adolescents use to manage their DM use in everyday life. Specifically, the questions aimed to elicit adolescents' efforts to pursue academic and social goals despite the temptations associated with DM use, as well as their ability to manage emotional responses while engaging with digital media. The questions were as follows:

What helps you manage situations in which you want to browse, play, or check something on one of your screen-based devices, but you need to do homework or study for a test?

What helps you calm down when you feel emotionally overwhelmed by something you read or saw on one of your screen-based devices?

When you meet with friends or family, what helps you stay focused on the interaction and not get distracted by messages or notifications popping up on your screen-based devices?

Analytic approach

We used a mixed-methods sequential design (Johnson and Onwuegbuzie, 2004), conducting a qualitative analysis first followed by a quantitative analysis. We used ATLAS.ti software (Scientific Software Development GmbH, Berlin, Germany) to conduct the qualitative analysis. Given our focus on identifying and classifying families of self-regulation strategies, we employed a constant comparative approach. This approach enabled us to group similar statements into mutual and exclusive codes and then group similar codes into broader categories (Glaser, 1965; Lou, 2022). This process constituted a three-tiered thematic organization, beginning with consolidating similar statements into codes (first-level codes), followed by organizing these codes into categories (second-level categories), and finally clustering the categories into broader families of strategies (third-level categories).

The qualitative analysis took place in the following steps: (a) two judges received the raw materials of the participants' answers and segmented them into statements independently. After segmenting their answers, the judges met to discuss and harmonize the segmentation. (b) The two judges named the theme of each segment independently and grouped statements with similar content. The judges then met to discuss the themes. They consolidated the names and criteria for the themes and discussed discrepancies in coding. The judges developed a list of initial codes that described all of the agreed-upon themes that emerged in the first analysis. (c) The two judges independently used the list to recode all of the themes into the agreed-upon codes. Themes that did not fit into the codes were discussed, leading to the creation of new codes. This process was repeated until all themes had an agreed-upon code. (d) Each independent judge went over the list of codes and grouped related codes into second-level categories. The judges met to discuss the second-level categories, establish criteria for each category, and create a list of second-order categories. (e) The two judges independently grouped the second-level categories into third-level categories and met to discuss the grouping until an agreement was reached. The discussions were supervised by the second author, who monitored the adherence to the analytic protocol and facilitated the discussion on discrepancies.

The quantitative analysis took place in the following order: (a) we decoded the qualitative data by converting the qualitative categories into numerical indicators (Tashakkori and Teddlie, 1998). Each instance of a self-regulation strategy was coded as a separate occurrence. Thus, a single response could receive multiple codes if it included more than one strategy. For example, participant 7 (Male, 14) reported, “I play online games with friends to relax, or I talk to my parents about it.” This response received two codes: for “actions aimed at regulating negative emotions,” and for “approaching others to process negative emotions.” (b) We decoded the numbers for each participant (e.g., how many participants used a specific code) so the analysis would reflect the report per participant rather than per quote. This step enabled us to reduce bias related to answers with several statements. (c) We examined the frequency of each category for each question separately to estimate how the use of self-regulation strategies varies across the academic, social, and emotional contexts. (d) Participants were classified into younger adolescents' (grades 7–8) and older adolescents' groups (grades 9–11) to reflect developmental differences between early and late adolescence, similar to the classification used by Puukko et al. (2020). (e) We conducted a set of chi-square analyses to assess age differences in the use of self-regulation strategies.

Qualitative analysis

The qualitative analysis aimed to classify the self-regulatory approaches that adolescents employ in the digital media (DM) context. However, not all responses described attempts to regulate digital media use. This included statements where adolescents described not experiencing any conflict, being unable to self-regulate the conflict, or responses that were unclear or irrelevant and, hence, were excluded from the analysis. While the constant comparative method was applied to all segmented responses, we organized this section by first presenting the analysis of responses that reflected attempts at self-regulation. We then describe the analysis of responses that did not indicate attempts at self-regulation.

Within the statements reflecting an attempt to apply self-regulation to manage the conflict, the constant comparison analysis revealed five primary third-level categories, presented below in their order of prevalence: (a) planning and organizing, (b) actions aimed at regulating negative emotions, (c) approaching others to process negative emotions, (d) cognitive regulation, and (e) external regulation. A description of the codes as well as the second- and third-level categories is presented in Figure 1. Table 1 presents the frequencies of third-level categories by age. Table 2 and Figure 2 present the frequencies of using the families of strategies divided by questions. A similar pattern of strategy use emerged in the academic and social contexts, where planning and organizing and cognitive regulation strategies were most prominent. In contrast, in the context of negative emotions aroused by DM use, adolescents more frequently relied on actions aimed at regulating negative emotions and on approaching others to process negative emotions. In the following section, we will describe each of the third-level categories with their respective second-level categories.

Category 1: planning and organizing

Planning and Organizing was the most commonly used family of strategies, reported by 70% of the total sample (72% of adolescents who indicated using at least one self-regulation strategy). This category refers to the proactive steps adolescents took to manage the conflict between their desire to use digital media (DM) and competing academic or social goals. Specifically, adolescents described planning ahead and organizing the situation in ways that helped reduce the temptation to engage with DM, for example by structuring their time, sequencing activities, or modifying the environment to support goal-directed behavior. These strategies reflect adolescents' active structuring of the situation to facilitate goal attainment. When others were involved, adolescents themselves initiated the regulation by intentionally seeking others' assistance as part of a planned strategy. In these cases, although others could take an active role (e.g., helping the adolescent concentrate or implementing technical restrictions), they did so at the adolescent's request and within a self-initiated regulatory process, reflecting a form of co-regulation. Therefore, these instances were not classified as external regulation, as the regulation was initiated and directed by the adolescents rather than imposed by others. Planning and Organizing manifested in four second-level categories:

Distancing

In this category, adolescents organized their environment in ways that reduced the immediate availability of DM devices. These strategies were described as helping decrease the temptation to use DM while engaging in other tasks. Distancing was the most commonly used strategy employed by the participants in the total sample. It involved closing or putting the device away, changing the device's setting to silent mode, placing the device out of sight, and making a group decision to put the device away. For example, Participant 30 (Male, 16) described, “I guess putting it [the device] in silent mode helps me, and also putting it away, like in a bag, pocket, or face-down on the table.” Several children described asking a parent to close or hold the device for them. We included this category here (rather than under external regulation) because the behavior was initiated by the child and was part of the deliberate attempt to change the context. For example, Participant 81 (Female, 14) stated, “I sometimes ask my parents to close my phone through Family Link (a parental control tool).”

Time management

This category reflects how adolescents planned and organized their time across DM use and other required tasks to prevent interference between them. Time management was composed of completing the task quickly to return to DM, finishing all tasks before using DM, allocating time for homework and using DM afterward, allocating time for DM and then completing the required assignments, and using DM as a break between assignments. For example, Participant 6 (Female, 15) stated, “I sometimes promise myself that if, for example, I study for an exam for 35 min, I will be able to watch 15 min of TV or something like that, and then I know that the faster I finish, the faster I get to the screen.”

Purposely engaging in a meeting

This category was unique to the question about social engagement. Adolescents reported that what helped them maintain social engagement, without getting distracted by the DM device, was trying actively to be involved, for example, by taking part and showing interest in the conversation topic. This strategy reflects purposeful planning of one's behavior during the interaction in order to structure the social situation in a way that increases attention to the ongoing interaction and reduces digital distraction. Participant 57 (Female, 15) described, “I'm starting to talk with the people around me.”

Studying with someone

This category was unique to responses to the question about academic assignments. Adolescents reported that planning to study in the presence of another person, such as a parent or a friend, helped them stay focused and complete their work. Descriptions of others' involvement suggested that adolescents were aware of the influence that another person's presence could have on their ability to concentrate and remain on task. They therefore intentionally chose to study with others as a way to create a more structured environment, increase their engagement with the task and reduce the likelihood of digital distractions. For instance, Participant 86 (Male, 14) described, “Usually when I do my homework, I sit with my parents and they help me concentrate.”

Category 2: actions aimed at regulating negative emotions

Sixty percent of the adolescents in the total sample reported using this family of strategies (62% of adolescents who reported using at least one self-regulation strategy). This family of strategies was the most frequently reported in the context of negative emotions aroused by DM use. It refers to self-initiated, active behaviors aimed at deliberately regulating negative emotions. It involved strategies adolescents used to reduce negative affect, either by shifting their attention away from the device to another activity or by engaging in alternative content or activities on a DM device that could help modulate their emotional state. Actions aimed at regulating negative emotions manifested in two second-level categories:

Taking an action that changes or calms the negative affect

Adolescents reported using a variety of distraction actions to change their negative feelings. This category was composed of distraction (e.g., thinking about or doing something else), using their body to calm physiological arousal (e.g., breathing or feeling the heartbeat), doing another activity, eating and drinking, going out for fresh air, resting, and engaging in a screen-free leisure outlet. For example, Participant 103 (Female, 13) described, “In that case, I would listen to music or play the piano since that's what usually helps me relax.”

Using another DM device to change or calm the negative affect

Adolescents reported applying various strategies to change their negative emotions by using other DM functions. Specifically, they reported watching pleasant content (such as funny content or shows they love); Participant 138 (Female, 15) described “looking for some funny and cute videos.” Some adolescents reported playing video games on a DM device alone or with friends. For example, Participant 7 (Male, 15) stated, “I just play computer/online games with my friends and it usually helps me relax.” Finally, some adolescents reported that negative feelings could be managed by browsing the internet aimlessly. For example, Participant 48 (Female, 14) reported, “I move to the next thing the phone shows me.”

Category 3: approaching others to process negative emotions

This family of strategies was specific to responses to the question regarding negative emotional arousal caused by content encountered on a DM device and was reported by 34% of the adolescents in the total sample (36% of those who indicated using at least one self-regulation strategy). Consistent with the concepts of interpersonal emotion regulation and co-regulation (Gable and Reis, 2010; Volet et al., 2009), these strategies reflect adolescents' self-initiated engagement with others to help manage, process, or make sense of negative emotional experiences through shared interactions. Specifically, adolescents described turning to others or seeking their assistance in dealing with negative emotions that arose from DM use. Adolescents reported engaging with different groups of people as part of this strategy:

Being helped by friends

Adolescents reported that seeking help from their friends by sharing their feelings or experiences helped them manage and cope with negative emotions. This second-level category involved being helped by a friend or talking with a friend. For example, Participant 145 (Male, 17) described, “I tell one of my friends about what I saw or read. We usually talk about the topic and that can help calm me down.”

Being helped by family

Adolescents reported that seeking help from their family members, such as parents or siblings, helped them cope with strong negative emotions. This second-level category involved being helped by a parent or a family member and talking with a parent, family member, or sibling. For example, Participant 33 (Female, 13) stated, “I usually share it with my mom or dad.”

Category 4: cognitive regulation

Thirty percent of the adolescents in the total sample reported using this family of strategies (31.5% of those who indicated using at least one self-regulation strategy). These strategies involve cognitive efforts to modify how adolescents interpret or appraise a situation in ways that reduce or inhibit the urge to engage with DM. Unlike Planning and Organizing strategies which involve proactively structuring the situation or arranging one's behavior in advance, cognitive regulation strategies operate at the level of internal thought processes. Adolescents described using strategies such as reframing the situation, reminding themselves of their goals, or engaging in self-talk to resist the temptation to use DM. Importantly, these strategies do not involve altering the external environment or sequencing actions in advance, but rather rely on regulating attention, thoughts, and interpretations in the moment. Cognitive regulation strategies manifested in three second-level categories:

Consideration of future consequences

In the context of academic assignments, adolescents reported being motivated to work on assignments instead of engaging with their DM devices by thinking about how helpful completing the assignment would be for their future, what they would gain by studying well, and the meaning of academic failures. For example, Participant 73 (Male, 13) reported, “I am reminding myself that if I do not study, I will fail the test.” In the context of social meetings, adolescents stated that thinking about their priorities and about the fact that they do not always have the opportunity to spend time with people they love, compared to the DM, which is always available, helped keep them engaged. For example, Participant 134 (Female, 16) stated, “I remember that I can be on DM at any time, but I can't do the same with friends and family.”

Thinking about future use of DM

Another way of changing their mindset and reappraising a conflictual situation was thinking about using the device after the assignment/social interaction was over. In this second-level category, adolescents resolved conflicts by thinking about future possibilities, rather than taking any action; thus, this concept belongs to the cognitive regulation rather than the planning and organizing strategies. For example, Participant 24 (Male, 15) described, “I'm just thinking that now I'll study a bit for the test/do homework and thus “earn” myself screen time.”

Suppressing thoughts related to the urge to use DM

Adolescents described direct attempts to cognitively resist the desire to engage with DM by trying to stop thinking about DM, ignoring reminders and notifications, or trying to stay focused on a task. For example, Participant 25 (Female, 15) stated, “I simply ignore all notifications.”

Category 5: external regulation

Only 7% of the adolescents in the total sample reported using this family of strategies (7.5% of adolescents who reported using at least one self-regulation strategy). Unlike strategies that involve deliberately approaching others to change the situation or to seek co-regulation of negative emotions, this family of strategies reflects externally imposed regulation that occurs without the adolescent's request or initiation. Specifically, adolescents described relying on parental monitoring and restrictions to resolve conflicts between DM use and other tasks. In these cases, responsibility for managing the conflict was delegated to parents, rather than adolescents actively engaging in self-regulation or intentionally seeking co-regulation. External regulation manifested at two second-level categories:

DM use is restricted by the parent

These adolescents reported that their parents actively restricted DM usage when they had to engage with an academic task. These behaviors involved, for example, taking devices away from the children during academic tasks (without being asked by the child to do so) or deciding how much time an adolescent could spend on DM on days when academic activities had to be done. For example, Participant 132 (Male, 13) described “my parents don't allow me to look at the phone.”

Other people's comments

Several adolescents reported that receiving direct requests or reprimands from other people concerning their DM use helped them to disengage from it during social interactions or when they needed to accomplish an academic assignment. For example, Participant 182 (Female, 14) stated, “I only succeed if others really ask me to.”

Strategies distribution across age groups

We conducted a series of chi-square analyses to examine age-related differences in the use of self-regulation strategies in the DM context. Table 3 presents the results of these analyses. Across the five categories of self-regulation strategies, one significant age-related difference emerged. Specifically, older adolescents were less likely than younger adolescents to report relying on others to process negative emotions (older adolescents: 25.7%, younger adolescents: 40.7%; χ 2 (1, N = 155) = 3.94, p = 0.047, ω = 0.16).

Although no statistically significant age difference was found for actions aimed at regulating negative emotions (p = 0.07), we conducted a follow-up analysis of the Level 2 strategies within this category to examine whether age-related differences emerged at a more specific level and may have been obscured in the broader category. This analysis revealed a significant difference, with a small effect size, in the use of DM to change negative affect (older adolescents: 29.7%, younger adolescents: 16.0%; χ 2 (1, N = 155) = 4.14, p = 0.042, ω = 0.16), suggesting that older adolescents were more likely than younger adolescents to use DM to regulate negative affect activated by DM. No other significant age-related differences were observed among the remaining Level 2 strategy within this category.

Adolescents who did not report using self-regulation strategies

Some of the adolescents in the sample reported that they did not experience conflict between DM use and other goals or were unable to regulate their DM use. Our analysis revealed that, with the exception of five participants who did not report any self-regulation strategies, the remaining participants in this category indicated the use of self-regulation in at least one context out of the three. Our analysis revealed four categories related to this response type, with percentages calculated based on the total sample:

Dysregulated DM use

Twenty-three percent of adolescents reported being unable to manage the conflict between the desire to use DM and other social or academic goals/demands. Adolescents reported that they kept using DM, gave up on engaging with social or academic activities, or did not attempt to disengage from disturbing content in the media.

Motivational factors

this category was specific to the question regarding staying focused during social meetings; 24% of adolescents reported having no conflict related to using DM during social interactions due to their own strong internal motivation to fully engage in these meetings (i.e., they enjoy meeting with friends or family and do not feel the need to use DM).

Situational factors

Eleven percent of the adolescents reported no conflict related to DM use due to the absence of one of the factors that can cause conflicts. For example, they did not have a personal smartphone or had no homework or exams. Other participants described not having a conflict between using DM and socializing because there was no social expectation not to use their device (e.g., everybody was using DM).

Personal characteristics

Ten percent of the adolescents reported having no conflict because they do not feel any temptation to use DM when engaging with other tasks due their personal characteristics (e.g., they never get distracted by DM devices or experience negative emotions because of DM use).

We did not find age-related differences in any of the above categories.

The current study was intended to identify what strategies adolescents use to manage conflicts related to the discrepancy between their desire to use DM and other academic or social goals, as well as when they experience negative emotions from something they were exposed to on DM. The qualitative analysis of adolescents' responses identified five families of regulatory strategies: (a) planning and organizing, (b) cognitive regulation, (c) actions aimed at regulating negative emotions, (d) approaching others to process negative emotions, and (e) external regulation. The quantitative analysis indicated that the use of self-regulation strategies varied by context. Specifically, similar patterns emerged in academic and social contexts, where planning and organizing strategies were the most prominent strategies, whereas in the context of negative emotions aroused by DM use, adolescents relied more on actions aimed at regulating negative emotions. The quantitative analysis also revealed age-related differences in relation to managing negative emotions aroused by DM use. Compared to young adolescents, older adolescents relied more on DM and less on others (e.g., family and friends) to process negative emotions. It is important to note that the strategies described reflect adolescents' reported regulatory practices. The study did not evaluate the long- or short-term effectiveness or adaptability of these strategies.

Families of self-regulation strategies in the DM context

The current findings suggest that adolescents are aware of the need to regulate their DM use, employ a wide range of self-regulation strategies, and adapt these strategies across contexts. When compared with established theories of self-regulation, the families of strategies identified in the current study align closely with several components of Gross's (2014, 2015) process model of emotion regulation. Specifically, Gross's model organizes regulation strategies along a temporal sequence and distinguishes among antecedent-focused strategies, which occur before emotions arise; cognitive strategies, which modify the meaning of emotional experiences as they unfold; and response-focused strategies, which aim to manage emotional reactions after they emerge.

Adolescents frequently described using antecedent-focused strategies, particularly planning and organizing their environment and time to reduce anticipated conflict surrounding DM use. Many participants reported intentionally placing their devices out of reach or structuring their study environments to minimize distraction and prevent DM from interfering with academic or social goals. These strategies appear to reflect adolescents' awareness that proximity to the device may undermine their ability to regulate their use. By proactively altering their environment, they reduced the intensity of the urge to use DM and prevented conflict between competing goals before it emerged (Liu et al., 2022; Volk et al., 2025). This emphasis on planning and environmental restructuring extends existing self-regulation models by highlighting the central role of situation selection and modification in digital contexts. Similar qualitative findings among university students indicate that strategies such as muting notifications, uninstalling applications, distancing devices, or restricting accessibility are perceived as more effective than relying on willpower alone (Arness and Ollis, 2023). Participants in the Arness and Ollis study similarly reported that awareness of negative consequences was often insufficient to regulate use once engagement had begun. The stronger reliance on antecedent-focused strategies may reflect the uniquely salient and rewarding nature of DM environments, which are intentionally designed to increase engagement and to capture attention (Cromheeke and Mueller, 2016; Domoff et al., 2024; Wegmann et al., 2018). Under such conditions, proactively modifying the environment may be more feasible than recruiting effortful cognitive control after exposure has occurred.

While planning and organizing were the most prevalent strategies described, some adolescents reported using cognitive-based strategies that resemble Gross's (2014, 2015) concept of cognitive reappraisal, in which individuals alter the emotional significance of a situation by changing how they think about it or about their ability to cope with it. Participants reported reframing the importance of academic or social demands in ways that reduced the urge to engage with DM. They also described using inner speech, reflecting on future consequences, and imagining future outcomes to manage temptation and remain focused on personal goals. In addition to reappraisal, some adolescents described suppressing thoughts about DM use to cope with conflict triggered by the device's presence. The deliberate use of cognitive processes to inhibit urges or modify motivational meaning reflects top-down self-regulatory capacities associated with effortful control (Nigg, 2017), which continue to mature during adolescence (Tervo-Clemmens et al., 2023).

Finally, adolescents described response-focused strategies aimed at regulating negative emotions that emerged during or following DM use. These strategies resemble Gross's response-focused strategies (Gross, 2014, 2015). They represent adolescents' efforts to use different behavioral means to return to an emotional homeostasis, some of which rely on intrinsic self-regulation strategies and others on others' ability to offer regulatory support through co-regulation (Nigg, 2017). The self-regulatory strategies adolescents described aligned with previously identified common self-regulatory behaviors, such as actions intended to distract from the negative emotions (Scheibe et al., 2015) and actions intended to increase positive emotions (Tugade and Fredrickson, 2007). Notably, the findings also underscore the use of DM itself as a regulatory tool. Adolescents described switching activities on DM platforms, such as watching calming videos, playing, or browsing the internet. This pattern aligns with the concept of digital emotion regulation, which refers to the deliberate use of DM to manage or curate (decrease or increase) both negative and positive emotions (Wadley et al., 2020).

Interpersonal regulation in the DM context

Although the current study's findings align with components of Gross's process model, they suggest that self-regulation in the DM context cannot be understood as purely intrapersonal. Adolescents' accounts point instead to a socially distributed regulatory system in which others function as active regulatory resources. Interpersonal strategies were used not only to manage negative emotions (e.g., seeking comfort or validation), but also to structure the environment in ways that reduce device availability, diminish the salience of digital cues, or lower motivation to engage (e.g., studying with peers, asking parents to remove the phone). In this sense, interpersonal self-regulation is not peripheral but central to how adolescents navigate DM-related challenges, extending and complementing intrapersonal frameworks by embedding regulatory processes within social relationships.

This pattern aligns with contemporary theories of interpersonal emotion regulation and co-regulation, which conceptualize self-regulation as fundamentally embedded in relationships across development (Paley and Hajal, 2022; Reeck et al., 2016; Zaki and Williams, 2013). At the same time, it reflects developmental models describing a gradual transition during adolescence from adult-initiated external regulation toward more autonomy-supportive, adolescent-initiated co-regulation (Sameroff, 2010). Consistent with this transition, adolescents in the present study reported actively recruiting instrumental support (e.g., parental management of device access), emotional support (e.g., processing distressing DM content), and attention deployment support (e.g., studying in the parents' presence) from parents, while also engaging peers as key regulatory partners for emotional processing, academic, and social engagement. Although adolescents frequently described self-initiated support seeking, some adolescents continued to rely on more direct external regulation, suggesting that external regulation is still present in the DM context.

The patterns described above may also have important implications for understanding effective parental involvement in the DM context. The relatively low prevalence of parental-initiated regulation compared to adolescent-initiated co-regulation aligns with research highlighting the benefits of autonomy-supportive parental involvement over restrictive or controlling practices (Bjelland et al., 2015; Meeus et al., 2019; Padilla-Walker et al., 2020). Although the present study did not directly assess parental media mediation style or outcomes, adolescents' reports suggest that parental involvement remained highly important, particularly for emotional regulation and environmental structuring, but was experienced as most effective when it responded to adolescents' needs and initiatives rather than being driven primarily by parental DM control. Adolescents frequently described turning to parents for help managing distress, maintaining focus, or organizing the environment in ways that reduced DM-related conflict. At the same time, they appeared to maintain autonomy not by avoiding parental support, but by retaining ownership over when and how parents became involved in the regulatory process. Given the substantial regulatory challenges posed by DM (Brand et al., 2016; Wegmann et al., 2018), parents' ability to remain available, responsive, and autonomy-supportive may play a central role in helping adolescents navigate the digital world successfully.

Regulation through DM

The results of the exploratory quantitative analysis suggested that older adolescents rely more on DM for emotion regulation than younger adolescents. While this difference can reflect the overall increase in older adolescents' use of DM for leisure, it may also reflect the development of purposeful use of DM for emotion regulation. The use of DM for self-regulation has been documented in both conceptual and empirical work, showing that individuals deliberately use different digital applications and modalities (e.g., social media, gaming, videos) to manage negative and positive emotions and to shape everyday affective experiences (Eschler et al., 2020; Smith et al., 2022; Wadley et al., 2020). At the same time, growing attention has been directed toward the potential long-term implications of digital emotion regulation. For example, using a mixed-methods design, Shi et al. (2023) found that although DM use may feel effective in the short term, it does not necessarily support sustained emotional regulation over time and may contribute to increased dependency and problematic use. Similarly, diary research by Scott et al. (2024) suggested that while digital regulation is associated with same-day emotional benefits, it may contribute to heightened negative affect on the following day.

In light of these findings, the increased use of DM for emotion regulation observed among older adolescents may reflect both an enhanced capacity to curate digital environments to meet emotional needs and a potential risk associated with growing reliance on this modality. Notably, the greater reliance on DM for emotion regulation among older adolescents observed in our study was accompanied by reduced reliance on others for emotion regulation. Although developmental models describe the increased reliance on intrinsic self-regulation as normative and expected (Paley and Hajal, 2022), in the context of digital emotion regulation, this shift may represent substitution rather than simple maturation. DM provides immediate, controllable, and predictable mood modification, whereas interpersonal regulation involves less certain responses (Swerdlow and Johnson, 2022). Its capacity for rapid emotional and sensory curation (Harrison et al., 2019) makes DM particularly efficient for short-term emotion regulation. Over time, however, the repeated subjective experience of success in regulating through DM may reinforce its use at the expense of interpersonal strategies, potentially limiting opportunities for empathy, emotion processing, and collaborative problem-solving, hence the longer-term emotional benefits of effective emotion-regulation (Shi et al., 2023). Thus, as adolescents age, digital emotion regulation may increasingly replace reliance on others, with possible negative implications for the development of flexible, more effective regulatory strategies.

Implications

The use of DM by children and adolescents has been increasing worldwide in recent years, encompassing a wide range of social, leisure, recreational and academic activities. Research on this topic has largely been focused on the issue of increased, problematic, and addictive DM use, with little knowledge of how to promote balanced and adaptive use. Our study results showed that adolescents were aware of the problems involved in dysregulated DM use and familiar with the idea of applying deliberate strategies to manage conflicts between DM and other activities. They described independently using a variety of strategies to balance their DM use with academic or social tasks as well as to regulate negative emotional arousal caused by DM use.

Moreover, the findings suggest that adolescents rely more on strategies involving planning and organization than on cognitive-based strategies such as reframing and inhibition when managing daily conflicts between DM use and competing social and academic demands. In many cases, this involved physically distancing themselves from devices to reduce the temptation to engage with DM. This pattern highlights adolescents' awareness of the need to intentionally apply self-regulation in the DM context, while also underscoring the challenges of relying on “in-the-moment” or effortful control strategies. Together, these findings suggest that effective self-regulation of DM use may require more structural environmental modifications and increased external support. In this regard, the continuous availability of caregivers as supporters in the self-regulation process may enhance adolescents' ability to structure their environments effectively and encourage interpersonal emotion regulation to process negative DM-related experiences. Finally, as reliance on DM for emotion regulation becomes more prevalent during adolescence, further research is needed to examine its long-term implications for wellbeing and interpersonal relationships, as well as how co-regulation can remain part of adolescents' broader emotion regulation repertoire.

Limitations and future work

Despite its potential contributions, the findings of the current study should be interpreted in light of several limitations. First, the quantitative analyses were based on the quantification of qualitative data within the same sample. Because the stability and validity of the coding categories have not yet been established across independent samples or different contexts, the quantitative findings should be interpreted with caution. Moreover, the age-related hypotheses focused on the Level 3 categories, rather than on the more specific strategies represented in Level 2. The follow-up analyses of the Level 2 categories within Actions Aimed at Regulating Negative Emotions were conducted to explore more nuanced age-related differences. As these analyses were exploratory rather than hypothesis-driven, their findings should be interpreted with caution and should not be taken to rule out other associations that were not systematically examined in the current study. Another limitation is that the way the questions were framed, and the contexts assessed may have directed responses toward planning and organizing strategies or contributed to biased reporting on external regulation. Future research should consider alternative question formats that capture a broader range of strategies, and assess self-regulation in contexts that were not assessed in the current study (e.g., sleep or internet safety).

In addition, the study relied on adolescents' online responses to open-ended questions. Such responses may have been influenced by social desirability or varying levels of attention and engagement. Face-to-face interviews might have yielded richer and more nuanced data. Moreover, relying solely on open-ended questions may have limited adolescents', particularly younger participants', ability to recall and articulate the full range of self-regulation strategies they use, or may have contributed to biased reporting of regulation initiated by others (i.e., external regulation). Future studies would benefit from incorporating more structured questions that present a comprehensive list of strategies that adolescents can choose from (e.g., Q-sort or questionnaires).

Several limitations related to the sample and scope should also be noted. The study was conducted among Israeli adolescents, and cross-cultural research is needed to examine whether the identified categories generalize to other cultural contexts. The relatively small number of 17–18-year-olds may have limited the representation of late-adolescent strategies, underscoring the need for longitudinal research to examine developmental changes over time. Additionally, information regarding neurodevelopmental conditions (e.g., ADHD) was based on parent report rather than standardized diagnostic assessment, and the study did not examine differences in strategy use by neurodevelopmental status. Future research should include adolescents with ADHD and other clinical populations who may be at heightened risk for problematic DM use.

Finally, to capture a broad range of self-regulation strategies across academic, social, and emotional contexts, the analysis did not differentiate between specific types of DM platforms. While this allowed for a cross-modality perspective, it precluded conclusions about platform-specific patterns. Moreover, focusing on conflicts between DM use and other goals may have overlooked situations in which DM supports social or academic aims and hence forms part of adaptive self-regulation strategies. Future studies should systematically examine self-regulation across different platform types (e.g., social networking, gaming) to determine whether strategy selection and effectiveness vary by platform characteristics. Future research should also assess the effectiveness of the identified strategies (or their problematic implications, such as in the case of digital emotion regulation), examine the development of DM-related self-regulation across the lifespan, and identify parenting practices that best support adaptive regulation in digital contexts. In particular, future research should employ ecological momentary assessment (EMA) and quasi-experimental longitudinal designs to examine how the use of specific strategies relates to adolescents' social, academic, and emotional-behavioral functioning over time.