Taking a Break: The Effects of Partaking in a Two-Week Social Media Digital Detox on Problematic Smartphone and Social Media Use, and Other Health-Related Outcomes among Young Adults

Given the pervasiveness with which smartphones have become integrated into modern society, their usage has been linked to a number of consequences, both positive and negative. With regards to positive consequences, smartphones allow users to make phone calls, send and receive text messages and emails, capture and display photos and videos, navigate to a destination, play games, surf the web, and access social media applications [3]. Hence, such features and functions allow users to communicate, connect, interact, and obtain information whenever they like [4,5,6,7]. However, despite their practicality and convenience, public and academic concern regarding the negative consequences of smartphones has mounted in recent years. Particularly, smartphones are said to have the potential to impair users’ health and well-being. For example, smartphone usage has been linked to impaired mental health (e.g., depression or anxiety; [8,9]), decreased self-esteem and well-being [10], and a number of other unhealthy lifestyle practices, such as disordered eating (e.g., meal skipping [11,12]), poor sleep [11,12], reduced physical activity and increased sedentary behaviour [13], and the use of drugs and alcohol [14], among others. Moreover, users are also more likely to engage in unfavorably viewed smartphone-related behaviours, such as phubbing (i.e., snubbing another individual in a social setting by paying attention to one’s phone instead of interacting with the person who is actually with them [15]), and develop nomophobia (fear of being without/not being able to use one’s smartphone [16]) or a digital fear of missing out (i.e., “fomo”; anxiety or fear of missing out on experiences their contemporaries are engaging in [17]).

Although many researchers urge the importance of not over-pathologizing smartphone use and highlight that many of the associations between smartphone use and negative outcomes are small [18], concerns regarding the negative impacts of smartphones (and their applications) continue to be discussed amongst greater society and by its individual members, so much so that many users are discussing their desires to revert to brick phones (i.e., those with limited functionality [19]) or spend time away from their smartphone [20], with many, somewhat ironically, sharing their journeys of disconnection on social media (which is typically accessed via smartphone). Additionally, many others are leveraging their smartphone’s built in (e.g., iOS Screen Time or Android Digital Well-Being) or third-party (e.g., Social Fever, App Detox) applications to better manage their smartphone time.

To date, several different terms have been referenced to describe periods of time where smartphone users are not engaging with the device. As Radtke et al. [21] (p. 192) pointed out, terms such as “abstinence, break, disconnection, detox, time-out, and unplugging” have been used. However, in their systematic literature review, Radtke et al. [21] postulated that the term digital detox should be used as an umbrella term under which all the aforementioned terms could fall. They also suggested that the Oxford English Dictionary’s [22] current definition of digital detox is insufficient, highlighting that “period of time during which a person refrains from using their electronic devices, such as smartphones, regarded as an opportunity to reduce stress or focus on social interaction in the physical world” is incomplete. Specifically, they suggested that a digital detox occurs any time an individual refrains from (or reduces) their usage of one or all their electronic devices (e.g., detox from smartphone only and still use your other devices or detox from all devices) or certain applications (e.g., all social applications or a single social application, such as TikTok), branded media, special features, interactions, and/or messages. They also highlighted that the detox itself need be completed voluntarily and intentionally, with the purpose of promoting health-related change [21].

Of all smartphone applications, social media applications, such as TikTok and Instagram, are among the most popular and time-consuming smartphone applications accessed by users, especially amongst younger generations who have grown up connected to the digital world [23]. Specifically, worldwide usage of social media, which are “internet-based applications that build on the ideological and technological foundations of Web 2.0 and that allow the creation and exchange of user-generated content” [24] (p. 60), has reached two hours a day, with most of this usage accomplished via smartphones [25]. Additionally, of all the applications available to smartphone users, researchers and larger society appear to be particularly concerned about negative consequences to users’ health that result from engagement with social media applications [21]. Thus, in addition to the considerable attention being paid to digital detox interventions restricting the use of the device (i.e., the smartphone), interest in more specific digital detox interventions, such as those that restrict the use of specific types of applications (e.g., social media applications), have garnered popularity. Particularly, given that smartphones have become an all but necessary component of everyday life, detoxing from social media instead of complete device abstinence or restriction may better balance the potential of obtaining improvements in health-related outcomes while still enabling users to continue, mostly uninterrupted, with daily life.

In a recent systematic literature review of intervention studies examining digital detoxing as the main behaviour change strategy, Radtke et al. [21] identified only 21 studies that had conducted digital detoxes focused on examining changes in health-related outcomes. Among these studies, the health-related outcomes investigated included sleep [26,27], life satisfaction [28,29,30,31,32,33,34], subjective well-being [28,29,30,32,33,34,35,36], anxiety [27,37,38,39], stress [27,33,34,40,41], depression [27,32,37], smartphone addiction [42], and social support [37]. Yet, Radtke et al. [21] noted contradictory findings (for example, Liao [27] reported a decrease in anxiety because of a smartphone detox, whereas Skierkowski and Wood [38] and Wilcockson et al. [39] found no effect) for nearly all the variables (excluding depression (Hunt et al. [37], Liao [27], and Tromholt [32] all saw improvements) and smartphone addiction (only measured by Ko et al. [42]) and identified several limitations and opportunities for future research. Notably, Radtke et al. [21] reported a lack of device-based measurements of smartphone and social media usage (i.e., lack of reliable and objective duration of usage data) and a lack of short- or long-term follow-ups. Moreover, they suggested that future research investigating social media digital detoxes should avoid focusing on the complete discouragement of smartphone and/or social media usage as this may not be realistic in everyday life, especially amongst younger generations who have grown up with both technologies. Rather, digital detoxes should be focused on encouraging users to develop healthy relationships with their smartphones and social media [43,44].

Among these studies, even fewer conducted social media digital detoxes (n = 13; [21]) despite their popularity amongst smartphone users [45] and their potential to positively impact health-related outcomes without disrupting everyday life. Specifically, social media digital detoxes have focused primarily on mental (e.g., life satisfaction, well-being, affect, boredom, stress, anxiety, and depression [28,29,37]) and social (e.g., connection, loneliness, social support, and pressure [36,37]) outcomes, and, again, mixed results have been reported. For example, with regards to life satisfaction, Hanley et al. [28] found no effect because of a 1-week social media digital detox, whereas Fiorvanti et al. [29] reported an Increase in life satisfaction after a 1-week Instagram digital detox, with Vanman et al. [33] reporting a decrease in life satisfaction after a 5-day Facebook digital detox. Thus, more studies examining mental- and social-health-related outcomes are needed.

Additionally, there is an even greater dearth of digital detox studies (none of which were social media, only digital detoxes) examining physical-health-related outcomes. For example, sleep has only been assessed by Dunican et al. [26], who limited usage of all electronic devices for 48 h and reported no effect on sleep quality, and Liao [27], who limited smartphone use for 2 weeks and reported improvements in sleep quality for those with anxiety and depression symptoms, once again showcasing the existence of contradictory findings. As such, additional inquiries into the effects a digital detox might have on sleep, and other physical health outcomes such as physical activity, sedentary behaviour, and eating behaviours, are warranted.

Finally, given that individuals might try some version of a digital detox because they may self-identify their use as being addictive or problematic, the lack of studies (Radtke et al. [21] only identified Ko et al. [42]) examining smartphone and/or social media addiction and whether taking a break would result in bringing about a positive impact is surprising and necessitates further investigation. Finally, among the existing digital detoxes, particularly social media digital detoxes, it is difficult to determine what is contributing to mixed findings studying the same health-related outcomes. However, it is evident to the authors of this study that there is a need to begin identifying the types of designs and characteristics (e.g., duration of detox, usage limits imposed) that are most effective.

The purpose of this exploratory study was to create and deliver a social media digital detox that addressed the limitations of previous detoxes (e.g., a lack of device-based measurements, lack of follow-up measurements, and unrealistic restriction instead of a reduction in usage) and explore its merits with regards to smartphone and social media addiction use and several health-related outcomes, including physical (physical activity, eating behaviours, and sleep), mental (life satisfaction, stress, and well-being), and social health (relationships) outcomes. Additionally, it was also desired to obtain a better understanding of participants’ experiences and perceptions of the digital detox to improve and maximize the effectiveness of future social media digital detox interventions. Specifically, the following research questions were asked: Does a social media digital detox impact smartphone or social media addiction? Does a social media digital detox impact physical, mental, or social health? What are participants’ experiences and perceptions of their social media digital detox?

The authors of this study assumed a critical realist approach, recognizing that reality is composed of three domains: the empirical (experiences that are observed and experienced), the actual (events, both observed and unobserved, that are generated or constrained by mechanisms), and the real (structures, powers, and mechanisms that produce or constrain events [46,47,48]). Thus, the authors acknowledge that, although only one true reality exists, individual interpretations and perceptions of this reality are shaped and influenced by perception, creating unique realities for all individuals.

A mixed methods research approach was used, whereby quantitative and qualitative data were gathered and integrated to combine the strengths of both techniques [49]. An embedded experimental design (two-phase model) was employed whereby qualitative data (i.e., semi-structured exit interviews) were collected after a quantitative one-group pretest–post-test experiment (with two-week follow-up) was carried out [50]. In doing so, the qualitative data can be used to help explain and contextualize the intervention (quantitative) results (i.e., RQ 1 and 2) while also unearthing additional information regarding participants’ experiences and perceptions associated with completing the intervention (i.e., RQ3).

A two-week social media digital detox, whereby the collective use of all social media applications (e.g., Facebook, Instagram, TikTok, Twitter) on participants’ smartphones was limited to 30 min per day, was carried out. This specific time limit was implemented in hopes that it would significantly reduce participants’ social media use on their smartphones but not be so restrictive that participants would be unable to complete the intervention successfully. The intervention period was preceded by a two-week period of normal use (i.e., no limits) to obtain a baseline of their overall smartphone and social-media-specific usages. Additionally, to see whether any changes that occurred during the intervention period remained after social media application limits were removed, a 2-week follow-up post-intervention period (i.e., limits were removed) was employed. All smartphone and social media application usage was objectively tracked using iOS’s(iOS 12) Screen Time, a built-in integration on all iPhones. Institutional research ethics board clearance (REB #22-116) was received prior to the start of recruitment and informed consent was obtained from all participants (see Figure 1 for participant flow).

Forty-three young adults were recruited from one department in a mid-sized university in Ontario, Canada via convenience sampling. Recruitment occurred via social media advertisement (i.e., departmental accounts, undergraduate, and graduate student society accounts) and email (i.e., mass emails to all students and in the monthly newsletter) in January 2023. Recruitment materials instructed interested students to contact a member of the research team via email. Upon contact, participants were provided with a letter of information and a copy of the consent form and asked to sign and return the consent form if they were still keen to participate, at which point an introductory meeting was scheduled.

Inclusion criteria were as listed: (a) undergraduate or graduate student in Kinesiology; (b) aged 18 to 30 years old; (c) iPhone user with Screen Time tracking turned on (or willing to turn it on for the duration of the study); (d) regular social media user (at least 1 h per day on social media applications); and (e) primary device for accessing social media was their iPhone. Participants also had to meet Radtke et al.’s [21] criteria of voluntary and intentional participation with the purpose of seeking health-related change. Participants were excluded from the study if they did not meet all inclusion criteria or if they were not willing to remove pre-existing Screen Time (or third-party application) limits to social applications for specified durations of the study (see Figure 1 for participant flow).

Of those that successfully completed the social media digital detox (i.e., were able to limit themselves to <30 min per day for the intervention period; n = 31), mean age was 21.16 (SD = 1.71 years; range = 18 to 26), with the majority currently completing undergraduate degrees (n = 25; 80.6%). More women (n = 21; 67.7%) than men (n = 10, 33.2%) participated in the study. Similar to Cowie and Braun [51], self-definition for ethnic/cultural origins information was utilized and resulted in the majority (n = 18; 58.1%) of participants identifying as White, while the remaining identified as South Asian (n = 5; 16.1%), Mixed (n = 4; 12.9%), Arab (n = 1; 3.2%), Chinese (n = 1; 3.2%), or Latin American (n = 1; 3.3%), with one participant (n = 1; 3.3%) opting not to disclose their ethnic/cultural origins.

At three separate timepoints (i.e., completion of baseline, intervention, and post-intervention periods), participants completed an online survey via Qualtrics. The surveys took, on average, 10–15 min to complete and contained questions pertaining to participants’ demographics (baseline only), smartphone addiction, social media addiction, physical activity, sedentary behaviour, sleep, eating behaviours, relationships, satisfaction with life, stress, wellness, and psychological well-being. Additionally, at each timepoint, participants were asked to retrieve data (i.e., total screen time and social application screen time) from their iPhone’s Screen Time integration for the previous two weeks.

Descriptive statistics for objective smartphone and social media use across all three timepoints are presented in Table 1. In order to successfully complete the social media digital detox (i.e., stay within the 30 min per day limit), the participants reduced their social media usage on their smartphone, on average, by 77.7%.

Qualitative analysis relating to research question two resulted in the identification of eight themes. The themes are briefly discussed below and presented in Table 4, with example quotes.

The qualitative analysis suggested that the participants experienced a range of feelings while partaking in the detox (Theme 1). Particularly, participants often expressed that they enjoyed the detox, often experiencing feelings of relief and decreased pressure to maintain their social media connections and/or presence. Conversely, some participants did acknowledge that the detox brought up feelings of disconnection, from friends and family, as well as what was going on in the world during that time. However, many participants were pleasantly surprised that the detox was perhaps easier than they thought it would be (Theme 2) and that the timing of the detox was likely a factor. Namely, most participants were in the midst of midterm season and expressed that being busy made it easier to adhere to the detox.

Numerous references were also made to the challenge of adjusting to the detox (Theme 3), be it the disruption to a participant’s normal routine, filling the 10 min between classes, or getting over the shock of the 30 min limit during the first few days. However, despite these initial challenges, most participants were able to adjust their routines, find their groove, and stay within their half hour of usage, so much so that many participants suggested that half an hour was a sort of manageable sweet spot, where they could still engage with social media but not get caught scrolling for hours (Theme 4). Nevertheless, there was consistent acknowledgment that, while social-media-related screen time was reduced during the detox period, overall screen time remained relatively high, with many participants saying they used other applications (e.g., games or entertainment applications) or other screens (e.g., laptop) more than they previously ever did (Theme 5).

Upon completing the intervention period, a great number of participants disclosed that they overindulged in social media for a short period of time (Theme 6). Interestingly, although some claimed to have done so somewhat subconsciously, many suggested that they were aware of the bingeing behaviour they were engaging in, that it only lasted a few days, and that their overall awareness of their social media usage increased as a result of participating in a detox (Theme 7). Similarly, other references to small changes in behaviours, such as adopting modified limits or establishing periods of downtime, were frequently expressed, suggesting that detoxing may have resulted in some small but positive residual changes.

Finally, the participants shared many valuable suggestions for future detoxes, with particular emphasis being placed on making detoxes realistic, sustainable, and personalized to each user, where possible (Theme 8).

A joint display of quantitative and qualitative findings for health-related outcomes is available in Table 5. It is important to note that, during qualitative interviewing, the participants were asked if they perceived any health-related changes in themselves as a result of partaking in the detox. As such, the participants focused on talking about health-related changes they experienced rather than discussing changes they did not experience.

At times, this display highlights the congruence between quantitative (frequentist and Bayesian) and qualitative data. For example, although the evidence was limited, there were quantitative data to support changes in stress across timepoints, which was supported by the qualitative data. In other instances, various incongruences are highlighted. For example, frequentist statistics suggest that the null hypothesis is rejected, but only with a small effect size, whereas the BF₁₀ suggests there is strong evidence to support the alternative hypothesis, which itself is supported quite nicely by qualitative quotes provided by many participants. Moreover, this joint display highlights additional nuances in the data. For example, physical activity and mindful eating are two outcomes that statistically showed no change across timepoints. However, qualitative interviewing revealed many instances where participants experienced or perceived changes in these outcomes. In some instances, for example, with regards to physical activity, it appears as though the participants may have engaged in more low-intensity physical activity and experienced more focus when engaging in moderate-to-vigorous physical activity, neither of which were captured by the quantitative measures. Similarly, with regards to eating behaviours, many participants perceived change in some aspect of mindful eating (e.g., reducing the speed at which one eats), but not in a sufficient number of mindful eating characteristics to generate differences across timepoints on a quantitative scale.

Consistent with previous studies that leveraged device-based [27,28,37,40,42,79] or self-reported measurements of smartphone or social media use [31,36], the participants in the current study experienced notable decreases in smartphone and social media use during the intervention period. However, this study’s use of a short-term two-week follow-up, which most previous studies have lacked, suggests that smartphone and social media usage may return to near pre-intervention levels within weeks, indicating potential backsliding.

Interestingly though, the detox resulted in reductions in smartphone and social media addiction for participants, which remained lower at two weeks post-intervention compared to the baseline. These results are similar to Ko et al. [42], who reported a significant reduction in smartphone addiction when smartphone use was limited. Yet, they also provided preliminary evidence that detoxing from social media on one’s smartphone has the potential to reduce not only smartphone but also social media addiction and that such reduction may be maintained, to some extent, for at least a few weeks.

With regards to physical-health-related outcomes, the quantitative results of the current study (frequentist and Bayesian) suggest that the social media digital detox had no significant effects on physical activity (specifically MVPA), sedentary behaviour, or mindful eating. To the authors’ knowledge, no other study has quantitatively examined digital detoxes in the context of the aforementioned outcomes. This dearth of research is somewhat surprising given that high levels of smartphone and social media use have been linked to decreased physical activity, increased sedentary behaviour, and unhealthy eating habits in previous non-experimental studies [80,81], suggesting that detoxing from social media could influence these physical outcomes. Despite a lack of statistically significant changes to physical activity, sedentary behaviour, or mindful eating, participant interviews do suggest that additional contextualization of these findings is needed. In particular, many participants expressed partaking in more low-intensity physical activity (LVPA; e.g., walks or household chores), which may not have been captured statistically because the quantitative variable measured MVPA, not LVPA. Additionally, although no statistically significant effects on sedentary behaviour or mindful eating were observed, a few participants expressed that they spent more time on their feet or less time sitting and adopted better eating habits. However, it is likely that not enough participants experienced (or were aware of) a reduction in their sedentary behaviour and changes to their eating habits to elicit statistical significance. Regardless, additional research examining the impacts of digital detoxes on physical outcomes is warranted, with a need for researchers to careful select the measures they are using (e.g., LVPA vs MVPA).

Conversely, significant quantitative improvements in sleep duration and quality, which were maintained to some extent during the post-intervention period, were observed, contradicting the findings by Dunican et al. [26]. However, some incongruence between frequentist and Bayesian interpretations was noted for sleep quality, with frequentist suggesting a small effect and Bayesian interpretations suggesting greater (i.e., moderate) evidence for the alternative hypothesis. Regardless, these findings are in line with experimental research by Liao [27] and many other non-experimental studies [82], which provide evidence of an inverse relationship between smartphone or social media use and sleep. Similarly, the study’s quantitative findings draw considerable qualitative support and confirmation, with many participants explaining that they fell asleep earlier and experienced better-quality sleep.

When trying to understand why participants experienced statistically significant improvements in sleep but no other physical activity outcomes, the authors of the current study postulate that the participants had fewer options with which nighttime screen time could be replaced (e.g., I went to bed earlier every single night because I was like, well, there’s nothing else for me to do) compared to daytime screen time (e.g., more options to pick from, such as studying or going on another screen). Additionally, given that the participants were sourced from a kinesiology department, it could be that the participants already had good and established routines with regards to their physical activity but not their sleep.

With regards to the mental-health-related outcomes, changes in satisfaction with life, stress, and perceived wellness were observed, and supported by qualitative findings, with participants often noting reductions in negative feelings and stress, as well as increases in positive feelings, productivity, and confidence. Similar to Hinsch and Sheldon [31], Fioravanti et al. [29], and Tromholt [32], who each conducted detoxes of varying lengths of Facebook or Instagram, the participants reported small but significant increases in life satisfaction at the end of the post-intervention period compared to the pre-intervention period. Conversely, these results contradict those of Hall et al. [30] and Hanley et al. [28], who found no effects, and Vanman et al. [33] and Vally and D’Souza [34], who observed decreases in satisfaction. When examining stress, the findings from previous research are mixed, with a few studies reporting no effect of a digital detox on stress [33] and many others reporting notable decreases [27,40,41], with the later in congruence with the findings from the current study. However, discrepancies between previous studies reporting reduced stress and the current study exist with regards to magnitude, with previous studies observing medium to large effect sizes compared to the current study’s small effect size (frequentist) and moderate evidence for support for the alternative hypothesis (Bayesian). Finally, similar to Brown and Kuss [79], who reported increases in mental well-being as a result of a 7-day social media detox, the participants in the current study experienced improvements in their perceived wellness. Yet, as has been noted with other outcomes, the size of the effect or strength of the evidence supporting this result is questionable, with frequentist interpretations being small compared to stronger Bayesian interpretations.

A small but significant improvement in the study’s only social outcome, supportive relationships, was observed. These findings received some support from participant interviews, with several participants suggesting that they inherently spent more time interacting with members in or outside of their household. However, these findings are in opposition to the social media digital detox studies by Hunt et al. [37], who found no effect on social support, and Stieger and Lewetz [36], whose participants reported greater social pressure during their detox.

In addition to using exit interviews to contextualize quantitative findings, it was important that this study be pragmatic and utilize these interviews to better understand participants’ experiences and perceptions of the social media detox, in hopes of providing suggestions for future social media detoxes. As a result, the authors were able to better understand how participants felt throughout the study, the effort it required for participants to detox, areas of challenge, obtain input on detox logistics, and identify areas for future improvement.

First, the authors assumed that the detox would be perceived to be difficult, and even unrealistic, for many individuals. As such, they anticipated (and experienced) difficulties recruiting. However, to the surprise of both the research team and the participants, two of the most commonly shared feelings associated with detox participation were enjoyment and relief, with many participants stating that the detox was easier than they thought it would be (Themes 1 and 2) and citing a range of positive feelings associated with their participation. Nevertheless, some participants did report feelings of disconnection and loneliness (Theme 1), which have previously been reported quantitatively [34,35]. Very few participants experienced these negative feelings to the extent that they terminated their participation or unsuccessfully completed the detox, with the majority of the participants indicating that they thought the study’s 30 min limit was challenging but doable. Thus, although nearly all, if not all, the participants said they experienced a period of adjustment (Theme 3; i.e., where they had to adjust to the detox’s reduced social media usage), most were able to overcome the trying first few days and successfully adjust their daily routines to reflect their reduced social media access.

Interestingly, many participants shared that their limited access to social media increased their perceived boredom during the intervention period, noting that small windows of time between classes or meetings were especially challenging. Such findings are consistent with Brown and Kuss [79], whose participants anticipated (before starting the intervention) that a reduction in social media usage would result in increased boredom, and Stieger and Lewetz [36], who quantified that a week-long social media detox led to increased boredom amongst participants. Again, similar to Brown and Kuss [79], the participants in the current study found themselves substituting social media use with other forms of screen time (Theme 5). Based on participants’ explanations, it is thought that this substitutive behaviour may not always occur consciously given the habitual nature with which younger generations engage with technology, especially for entertainment [79].

Additionally, as Radtke et al. [21] reported, only a limited number of digital detox studies have included follow-up measurements [36,37] of their outcome variables. As such, this exploratory study fills a significant gap in the literature by conducting post-intervention testing two weeks after the conclusion of the detox. Although qualitative accounts from participants suggest that many excessively indulged (i.e., binging) in social media for a short duration immediately following the intervention (Theme 6), comparisons of quantitative means pre- and post-intervention indicate that both addiction and all the health-related outcomes studied showed positive or neutral improvement. Thus, at minimum, participating in the detox did not negatively impact any quantitative outcomes amongst the participants in the current study, and any improvements made during the intervention period were maintained at least to some extent. Moreover, the qualitative findings from the exit interviews support the quantitative improvements observed during the intervention period and maintained during the post-intervention period. Namely, participants acknowledged that they became more aware of their social media habits and have already taken small steps (e.g., modifying limits or establishing periods of down time) to regulate their usage.

Finally, the participants provided several practical suggestions, based on their experience partaking in the detox, that could be incorporated into future detoxes to increase their overall efficacy and, perhaps more importantly, participant buy-in. Generally, these suggestions can be grouped into four categories. First, although most participants noted that limiting social media use to 30 min a day was difficult but reasonable, many acknowledged that, if they were to continue restricting their usage, they would opt for slightly more time. Thus, there is potential cause to conduct detoxes that are slightly less restrictive (e.g., 45–60 min of social media use per day) and to compare their effectiveness and buy-in to those of shorter durations. Moreover, one participant did point out that, instead of applying a one-size-fits-all approach to detox (i.e., all participants reduce their usage to the same amount of time), personalized limits (e.g., reducing each participant’s use by a specific percentage) could be more impactful and result in more buy-in from heavy users. Second, similar to Brown and Kuss [79], it was suggested that encouraging or enforcing participants to limit their social media application notifications could assist participants to complete the intervention period. Specifically, doing so would create less temptation to access social media simply just to see what caused that notification. Third, instead of restricting usage of all social media applications, many participants noted that certain applications are more destructive than others (e.g., many mentioned TikTok) and that limiting only those that were viewed negatively would be more realistic and, again, be easier for heavy users. Finally, during the intervention, some participants said that they opted to delete or sign out of some or all of their social media applications to reduce temptation, with several others suggesting that, in hindsight, the detox would have been easier if they had done so as well.