Introduction

In modern society, the use of smartphones and social media is enormously widespread with about 66% of the world’s total population owning a mobile phone and about 53% accessing social media apps (such as Whatsapp, WeChat, Facebook, and Instagram) [1]. In Europe, in 2021, 83% of individuals used their smartphones to access the Internet in the previous 3 months and about 60% used the Internet to participate in social networking sites or in calls and video calls [2]. Moreover, the EU Kids Online 2020 report indicated that most European children prefer smartphones to access the Internet as constant connectivity and availability are guaranteed [3].

Despite the positive opportunities offered by technological devices and services (for example in terms of social connection and information searching), there is an ongoing debate about the negative consequences for everyday life of unregulated use of smartphones [4•]. Thus, over the last decade, problematic smartphone use (PSU) (variously termed smartphone use disorder, smartphone addiction, etc. [5]) has emerged as new potential problematic behaviour.

Problematic Smartphone Use

Given the emerging research area of PSU, its definitions are still evolving [6–10]. PSU is broadly defined as an uncontrolled and compulsive (over)use of the smartphone linked to negative consequences (e.g. withdrawal, impeded user productivity, social relationships, physical health) which can result in the impairment of daily functioning of the user [6, 11–13]. The prevalence of PSU among children and young people is 23.3% (based on 31 studies with a prevalence between 10 and 30%, see Sohn et al. [14] for a systematic review and meta-analysis). Although PSU is characterized by shared “symptoms” with addictive behaviours (e.g., tolerance-like and withdrawal-like phenomena and loss of control) (see De-Sola Gutiérrez et al., [13] for a review), its recognition as a potential behavioural addiction is debated [9, 10].

From the framework proposed by Billieux and colleagues [12, 15], PSU is described as a multi-faceted phenomenon entailing a variety of dysfunctional manifestations (addictive, antisocial, and dangerous use), each being associated with distinct developmental pathways, including (1) excessive reassurance (e.g. the need to maintain relationships and obtain reassurance from others), (2) impulsivity (mainly driven by poor impulse control, which in turn might result in uncontrolled urges and dysregulated use), and (3) extraversion [e.g. the need for stimulation and a high sensitivity to rewards, which in turn might result in a wide range of risky behaviours (e.g. sexting and phoning while driving)].

In its infancy, smartphone was studied as a holistic phenomenon without considering the app used. More recently, literature has also began focussing on PSU in relation to technology features, such as various mobile apps, social networking sites and instant messaging, gaming, Internet addiction/app addiction, and task context (see Busch and McCarthy for a recent review [4•]). In addition, previous research showed that PSU is also related to the setting in which the smartphone is used [8, 16, 17]. Indeed, PSU in the classroom has been associated with procrastination [18], while PSU in the bedroom during normal hours of sleep has been associated with poor sleep quality and sleep disorders [19]. Thus, recent research has highlighted the role of specific types of apps available on the smartphone and the setting in which the smartphone is used for the development of PSU.

Several studies [20••, 21] suggested that smartphones are predominantly used for social purposes (i.e. for the use of instant messaging apps and social networking sites). In line with recent arguments about the importance of understanding “what” users do on their smartphone and which types of app are more likely to contribute to the development of PSU [20••, 22], the aim of the current systematic review is to describe to which extent PSU is associated with problematic social media use (PSMU) considering the problematic use of social media apps (e.g. Instagram, Facebook, WhatsApp, Snapchat, WeChat).

Problematic Social Media Use

As in the case of PSU, PSMU (variously termed social media disorder, social media addiction, etc. [23]) has not been recognized as a proper behavioural addiction. Rather, it has been defined as the use of social media characterized by “addiction-like” symptoms and causing impairments in users’ daily life in terms of school and job failure and conflicts with family and friends [24]. PSMU has been variously conceptualized, termed, and assessed [23]. A substantial number of early studies adopted the six core criteria of the addiction component model (i.e., salience, mood modification, tolerance, withdrawal, conflict, and relapse; see [25, 26]) or reflected the 9 criteria proposed for the assessment of Internet gaming disorder, such as in the case of the Social Media Disorder Scale that includes three additional criteria (namely problems in important life domains, displacement of activities, and deception) [27]. Using the latter scale and a cut-off of 6 symptoms (instead of 5 as in the case of IGD) [28], the recent international report of the Health Behaviors in School-aged Children (HBSC) survey indicated a prevalence of PSMU in adolescents of 7% across Europe and Canada [28]: that is 7% of adolescents reported 6 or more symptoms adapted from the criteria for Internet gaming disorder (i.e. preoccupation, tolerance, withdrawal, persistence, escape, conflict, problems in important life domains, displacement of activities, and deception [29, 30]). However, the prevalence of PSMU tends to vary widely across cultures and in methods of assessment [31]. PSMU is an umbrella term covering problematic use of a variety of websites and applications, such as blogs, YouTube, traditional social networking sites (SNSs, such as Facebook, Instagram, and Snapchat) as well as instant messaging apps (such as WhatsApp and Facebook messenger), which are more likely to be accessed by smartphones. Indeed, there is evidence that “general” PSMU is associated with PSU. However, it has been suggested that the problematic use of specific social apps (such as smartphone-based applications like WhatsApp) might be more strictly related to the PSU [32••].

Aim

It has been argued that comparing problematic use of the device and of the types of applications is crucial because certain online activities may be more problematic than others [33••]. The debate about the overlap and the differences between “addiction to the Internet” versus “addiction on the Internet” was raised, about 20 years ago, by Griffiths [34], who suggested that problematic Internet users use the Internet to fuel other addictive behaviours, such as gambling, compulsive shopping and sex, gaming, and social networking sites use, rather than being addicted to the Internet per se. Similarly, there is an ongoing debate about the overlap and differences between generalized problematic use of smartphones as a medium (addiction to the smartphone) and problematic use of specific apps available on smartphones (addiction on the smartphone) [35•, 36], that is the smartphone is the medium of one or more problematic activities. Beyond these different views, Barnes and colleagues [33••] have highlighted that research about smartphones and social media has tended to follow two distinct routes or “streams of research”. However, the problematic use of smartphones and social media is related, mostly because social media are often engaged via smartphones [37]. Recently, an increasing number of studies have been explicitly analysing the overlap between PSU and PSMU using different approaches. Therefore, the aim of the current article is to provide a systematic review of the studies that have investigated the association between PSU and PSMU, thus informing the development of future research.

Methods

This systematic literature review follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines (2009 [38]). From November 2020 to January 2021, we searched four comprehensive bibliographic databases: PubMed, Web of Science, Google Scholar, and EBSCO that included Academic Search Complete, PsycARTICLES, and PsycINFO for articles published in English after 2007. The release of the smartphone occurred after 2007; therefore, we have included studies published after this year. We did this in order to assemble data from participants using primarily smartphones rather than older mobile phones. The search was conducted using the following algorithm: smartphone (cellphone OR mobile phone) AND use disorder (overuse OR addict* OR abuse OR use severity OR problematic OR dependence), AND social media (OR social networking site OR SNS) AND problematic use (OR usage OR disorder OR addict*) OR Internet communication disorder.

The inclusion criteria for eligible studies in the present review were the following: (i) having been published in scientific journals from 2007 to January 2021; (ii) being written in English; (iii) containing enough quantitative empirical data; and (iv) reporting the association between the PSU and PSMU. Moreover, studies were excluded if they assessed problematic Internet use, in general, and the frequency of use of social media or smartphone but not of problematic uses. Systematic reviews and meta-analyses were not included.

Study Selection

After performing the aforementioned searches, a total of 4276 hits (Google Scholar n = 1119; Web of Science n = 825; PubMed n = 766; EBSCO n = 1566) were initially identified. The flow diagram in Fig. 1 details the selection process. Following the initial literature searches and a first removal of duplicates (n = 23), each study title and abstract was examined for eligibility (n = 4253) and 4070 publications were excluded because of unsuitability for the present review based on the inclusion and exclusion criteria. Consequently, we collected 183 articles (Google Scholar n = 96; Web of Science n = 38; PubMed n = 14; EBSCO n = 38) and 3 articles, reported in references lists, were hand searched. Full texts of all 186 potentially relevant articles were then retrieved and further examined to determine whether they could be included in the review. From 186 articles, 173 were excluded because they did not meet one or more inclusion criteria: assessing problematic Internet use, in general (n = 9); assessing the frequency of social media use and/or not assessing problematic social media (n = 77); assessing non-problematic smartphone use (n = 83); same sample (n = 2); and missing requested data (n = 2). Following this process, a total of 13 articles were identified for inclusion in the present review. All studies were double screened by two authors (CM and FM) for inclusion. Then, the selected studies were double coded by the same two authors, extracting (1) the identification of the study (authors, year of publication, national setting); (2) the characteristics of the sample (sample size, mean age and range, gender ratio); (3) the design of the study (cross-sectional vs. longitudinal design); (4) the assessment of PSU and PSMU (operationalization, measurement); and (5) the relationship between PSU and PSMU (correlations and paired t-test). There were two cases of disagreement among coders that were discussed until agreement was met. If correlations were not reported, we contacted the corresponding authors to ask for an ad hoc analysis (if no response was received, a second e-mail was sent 2 weeks after the first one; we received the requested data for 1 out of 3 requests). Table 1 provides a summary of details regarding characteristics of included studies.

Fig. 1
figure 1

Flow diagram (adapted from Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. https://doi.org/10.1136/bmj.n71)

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Table 1 Journal articles that have examined the relationship between Problematic Smartphone Use (PSU) and Problematic Social Media Use (PSMU)
Full size table

Description of Included Studies

The first study explicitly showing the association between PSU and PSMU was published in 2015. The remaining articles were published after 2016 (mostly in 2020), confirming the newness of research interest in this topic. First, socio-demographic characteristics of the study samples are described in order to provide the overall context of the current summary of the literature.

With regard to gender, samples were overall equally distributed across males and females with a slightly observed majority of females in a few studies [e.g., 33••, 39]. Two studies reported correlations between PSU and PSMU by gender with a similar pattern of associations among males and females [20••, 52]. Nevertheless, higher levels of PSMU are commonly detected among females [57] but, since smartphone use includes a variety of online activities, it might be interesting to explore whether PSU shows different patterns by gender based on preferred apps.

With regard to the national setting, three studies used German-speaking samples, three studies were carried out in China, two samples were from the USA, two from Turkey, two from Iran, and one from Hungary, thus, suggesting a certain degree of heterogeneity by country and none used a nationally representative sample. The different national settings of the reviewed studies should be acknowledged as social media apps are differently spread among different countries and the shared cultural use of technological devices and social media may vary. As an example, WeChat is a widespread form of social media in China whereas Instagram and Facebook are more commonly used in Europe and in the USA [58]. Moreover, although it is not possible to detect a clear trend of associations between PSU and PSMU across regions, nor to compare the findings across studies, it should be noted that the strongest association is observed in a sample from the USA [40] and the lowest in a sample from Iran [45], when considering “general” PSMU. One possible reason for this may be related to recent global statistics [59] showing that the penetration rate of mobile social networks use is higher in Eastern Asia (70%) and Northern and South America (61%) and tends to be lower in Western Asia and Europe (about 45%).

With regard to the age range of the samples, it varies considerably. As an example, the German-speaking samples included smartphone users from 12 to 75 years of age [20••, 32••, 52]. Only 2 studies were focused on adolescents [45, 49], whereas in the remaining studies, the sample mainly comprised young adults. Despite the large range of ages of some samples provides an overall picture of the phenomena, adolescents and adults might engage in different social media and might have different addictive tendencies towards the digital technologies [52]. In 2019, the European School Survey Project on Alcohol and Other Drugs [60] reported that almost all students aged 15–16 years (94%) used social media in the previous week (e.g. WhatsApp, Twitter, Facebook, Skype, Blogs, Snapchat, Instagram, Kik) with about half (about 46%) reporting self-perceived problems with such use (in terms of too much time spent online and family concerns), thus suggesting that technology-related behaviours are relevant among adolescents. Future studies focussing on different age groups and highlighting whether and how specific social media are more likely to be associated with PSU for youth as compared to adults are warranted.

Methods of Assessing Problematic Smartphone Use and Problematic Social Media Use

Six studies used the Smartphone Addiction Scale (SAS; 3 used the original version by Kwon et al. [50]; and 3 used the German version by Montag et al. [47]). The SAS is a 10-item single factor scale, derived from a longer 33-item version, assessing addictive-like symptoms, such as daily-life disturbance, positive anticipation, withdrawal, cyberspace-oriented relationship, overuse, and tolerance. In its original version, the SAS includes a specific item related to the use of social media: “Constantly checking my smartphone so as not to miss conversations between other people on Twitter or Facebook”, whereas the item ends with the word “conversations” in the German version. Accordingly, the 3 German studies used an adapted version of the SAS in order to assess WhatsApp, Facebook, and Instagram Disorders, by replacing the word “smartphone” with the name of each social media and discussed the overlap between PSU and specific PSMU, finding higher correlations between PSU and problematic WhatsApp use as compared to problematic use of Facebook, Instagram, and Snapchat.

Three studies [35•, 45, 53] used the Smartphone Application-Based Addiction Scale (SABAS [46]), which assesses the risk of being addicted to smartphone applications [based on the six addiction criteria proposed by Griffiths [25] (salience, mood, modification, tolerance, withdrawal conflict, and relapse)] and the Bergen Social Media Addiction Scale (BSMAS [26]) that assesses the same six criteria of the addiction component model in relation to general social media use.

The remaining studies used 4 different scales to assess slightly different constructs akin to PSU, that is mobile phone addiction and dependency, cell phone overuse, and addiction to smartphone (see Table 1 [33••, 39, 40, 43]). Moreover, either a validated scale (Social Media Disorder Scale [27], Chinese Social Media Addiction Scale [54, 55]) or ad hoc measures [39, 43] or an adaptation of the scale was used to assess PSMU.

Overall, PSU and PSMU are variously conceptualized using similar theoretical frameworks and are assessed with measures reflecting the same “addiction-like” criteria. One study [32••] demonstrated the overlap between symptoms of PSU and problematic WhatsApp use on item level of the SAS, providing also promising insights about the likelihood of problematic Instagram and Facebook use to be separated constructs from PSU. Further studies are needed in order to verify the overlap of smartphone- and social media–related symptoms item by item.

Association Between PSU and PSMU

The present review was aimed at synthesizing the association between PSU and PSMU providing an estimation of their correlation. Cohen [61] proposed conventional values as benchmarks for what are considered to be “small”, “medium”, and “large” effects (r = 0.1, 0.3, and 0.5, respectively). Overall, following these benchmarks, the associations between PSU and PSMU range from medium to large across the included studies. Specifically, the 18 correlations observed in 12 studies indicated that 7 correlations ranged between 0.30 and 0.50 (i.e., the associations between PSU and problematic Snapchat and Facebook use and social media, in general); 8 correlations ranged between 0.50 and 0.70 (i.e., the associations between PSU and social media, in general, or Facebook and Instagram); and 3 correlations were higher than 0.70 (i.e., the associations between PSU and problematic WhatsApp use and social media, in general). Only three studies examined the multicollinearity concluding that it was not a concern [33••, 39, 40]. However, given the large observed associations, future studies should include a formal test for multicollinearity.

Overall, higher associations were found in studies comparing PSU with PWU and social media, in general, followed by Instagram and Facebook. First, although accessible also via laptop-based browsers, WhatsApp is a messaging app specifically developed for text messaging on smartphone that is susceptible to promote the development of PSU [32••] (for a review about the addictive features of WhatsApp and other apps, see Montag et al. [62]). Second, when participants complete a scale assessing problematic use of social media or SNS, in general, they may tend to think about the apps they use the most, but these might be different across users, countries, and studies. This could be one of the reasons why the range of associations between PSU and PSMU, in general, tend to vary considerably across studies.

Twelve out of 13 studies employed a cross-sectional design: it could be that PSMU contributes to worsening the levels of PSU as social media are predominantly used on smartphones and they might be addictive per se because they are specifically designed to prolong engagement time [62, 63]. However, the alternative explanation may also be plausible in that the constant availability and portability of smartphones might induce users to repeatedly check notifications and feel the social pressure to send and reply to texts and access social media. The only longitudinal study [35•] highlighted the effect of PSU and PSMU in predicting psychological distress but the longitudinal relationships between PSU and PSMU remain unclear. As a note, Barnes et al. [33••] did not report the correlations between constructs but highlighted that PSU was higher than PSMU in their sample because, beyond social media use, PSU also covers other potential problematic behaviours (such as watching videos and gaming). In addition to the variety of available apps with specific features, PSU may also lay in its embedded elements that may drive users to endless scrolling, repeated unblocking of the screen and need for touch [64], checking habits, and compulsively accessing different apps due to poor impulse control [e.g., 65,66]. Technology features, such as need for touch, unlimited mobile data, personalization of components and capacities, speed, portability, and accessibility, have been found to be associated with PSU (see Bush and McCarthy [4•] for a systematic review and meta-analysis).

Conclusions

Overall, the large associations observed between PSU and PSMU indicate that the two phenomena are partially overlapping mostly because the smartphone is a common medium to use social media, especially concerning instant messaging apps like WhatsApp [37, 63]. Despite the evidence that engagement in social media/networking sites may cover the main amount of time spent on smartphones [63, 67], the overlap between the two problematic uses is partial, likely because smartphones allow the use of a number of other applications and potentially problematic activities (including web surfing, gaming, series watching, pornography, gambling). Moreover, social media can be also accessed through other mobile devices (such as tablets) [68] and non-mobile ones (such as desktop computers and laptops)—which are not characterized by the same capabilities of smartphones), thus suggesting that the behaviour of social media use, rather than the used medium per se, might be problematic [e.g., 67,69]. However, only a few studies on PSMU reported the preferred device used by participants to access social media [e.g., 70]. Future studies should aim at analysing whether people differ in their levels of PSMU depending on the medium they use the most (the smartphone vs. other devices) in order to clarify whether mobile features actually contribute to the risk of developing problematic behaviours [71]. Moreover, more research on what social media activities (such as photo editing, scrolling, chatting, video making/watching) can become more problematic if done on the smartphone compared to other devices might be interesting [see for example 72,73]. Importantly, studies should consider that the context in which people use technology devices (when driving, working, studying) can make a specific activity more or less problematic [e.g., 4•, 67]. In this view, the definition of PSU itself could be updated considering the actual negative impact of maladaptive smartphone use on daily life. Thus, according to Montag and colleagues [62], the content or the preferred online application and the specific device used should be taken into account when investigating PSU and PSMU.

Results of the present systematic review indicate that the definition and assessment of PSU and PSMU may influence the degree of overlap between the two phenomena, thus suggesting the need for accepted criteria and shared construct validity of online behaviours [74]. Our work is thus relevant in relation to the current debates about the conceptualization of PSU and suggests that this problematic behaviour should preferentially be studied with a focus on specific types of apps used rather than as a more holistic phenomenon [4•]. For example, given that WhatsApp or other instant messaging services are strongly associated with smartphone use (more than other social networking sites), future studies are invited to specify the types of social media they refer to when assessing PSMU.

Some conclusions can be drawn. First, we found a partial overlap between PSU and PSMU, meaning that differences (in addition to commonalities) should be take into account.

Second, a number of correlates have been found to be associated with both PSU and PSMU [56], including adverse psychological consequences and social and individual characteristics [e.g. 14, 75, 76]. Therefore, it might be useful to look at psychological profiles of users who are more likely to suffer some distress due to smartphone and social media use, thus highlighting further differences, shared mechanisms, and factors and consequences for well-being [4•, 33••, 56].

Third, comparisons across countries should be cautiously looked at and studies using representative samples are needed. Lastly, self-reported use of smartphone and social media may not be accurate [e.g., 77] and it is very common that people use more than one social media on their smartphone, thus increasing the probability of a multiplier effect in problematic symptoms. Therefore, future studies would benefit from the use of objective data gathered from smartphone applications and social media [78] in order to combine symptoms of problematic use with the actual and cumulative use of different applications.

In conclusion, giving the overlapping nature of the phenomena, studies could consider focussing on PSU and/or PSMU taking into account the precautions described above. Depending on the specific goals or research questions, researchers could consider the utility of controlling for PSMU when assessing PSU (and vice versa), especially if interested in the mechanism underlying problematic behaviours.