Attention is a scarce finite resource implicated in a variety of cognitive processes determining individual action and volition (1) that can be deployed externally (e.g., focus on the shape of a certain stimulus) or internally (e.g., focus on neutral or positive thoughts) (2). In the digital age, and particularly in the current pandemic era, which has shifted education and employment to remote learning and working, respectively, attentional resources are consistently challenged for engagement (3, 4). Concerns have been raised that the increased pressures for digitally juggling remote working with social, recreational, and information demands may be contributing to difficulties maintaining a healthy work-life balance (5) and the onset of mental health difficulties such as occupational burnout (6, 7). Additionally, online social spaces are influencing users with persuasive design (i.e., rolling feeds), prompting high cue reactivity and prolonged use of and overreliance on digital devices (8–11). Multitasking, multiple device use, and frequent attentional shifts are salient behaviors potentially leading to digital information overload (12–14).

Smartphones are ubiquitous digital devices that offer multiple communication affordances to half of the world's population (15), and may interfere with how attentional resources are allocated, constituting an emerging area of research (16–19). Increasing evidence suggests that smartphone use triggers frequent interruptions and breaks from main tasks, further interfering with cognitive processes and ability (20–24), cognitive functioning (25–28), and associated with distraction and compromised performance (26–28) resulting in sub-optimal learning among young people (29, 30). Disruption from smartphone use is even more prominent within classroom environments (31–33), hindering academic achievement due to interference with primary tasks (12, 34) and in less engaging academic contexts, prompting lower motivational levels and comprehension (12, 35, 36), task performance (37), and chronic media multitasking (12). Smartphone interruptive notifications are frequent external triggers (38) which disrupt daily activities and have even been associated with mood disorders mediated by boredom proneness (39).

Given the numerous advantages of smartphones which provide constant internet accessibility, distraction has become frequent and endemic among smartphone users, potentially reinforcing more habitual or compulsive smartphone use (40). Distraction has been traditionally defined as an emotion regulation coping strategy implicated in shifting focus to a non-threatening situation or thought to reduce emotional distress and negative affect (41–45). Smartphone distraction (SD) may be caused by external triggers, such as notifications, intrusive thoughts, or cognitive salience of smartphone-related content to avoid or regulate emotions (26, 46–48). Fear of missing out (FOMO: missing out on positive recreational experiences of others) appears to be a main driver for several forms of problematic technology use (49), including smartphone use (50) currently exacerbated by the impact of the pandemic and social isolation (51) and driving attentional bias and distraction from online content to fulfill control needs (52).

One of the most prominent models of attention and its orientation has been proposed by Posner (53), viewing the attentional system as having the possibilities to shift, orient, and disengage as a biased response. Based on Posner's attention networks model (53), as adapted by Wu and Cheng (54) for educational contexts (see Figure 1), SD is conceptualized within the present study as the result of a reaction to exogenous (orienting system) or endogenous cues (alerting system) or as the result of a conflict amongst these two networks that are competing for attentional resources. For the occurrence of distraction, the exogenous cues (orienting system) are triggered by auditory/visual signals, which can take the form of smartphone notifications in smartphone use. The endogenous cues (alerting system) are the bottom-up signals in the form of expectancies, worries, and lingering thoughts leading to distraction or daydreaming. The executive system is implicated when conflict arises between the exogenous and endogenous cues, leading to attention discontinuity and therefore poor attention deployment, prompting inhibitory or executive control difficulties (55). Distraction appears therefore to be the result of disruptions or interruptions in one of the three attention networks mediated by smartphone use (29, 39, 54).

Distraction may be psychologically explained by the control model of engagement (52), a theoretical model integrating elements from distraction conflict theory (56), theory of social facilitation (57), and perceptual control theory (58), supporting that online engagement partially occurs to control online content, relationships and presentation online, causing attentional bias toward online stimuli and distraction from daily activities. Distraction may be facilitated by the presence of others online (56, 59), prompting interaction and leading to heightened engagement or shallow processing when involved in parallel cognitively demanding tasks. Beyond perceptual conflicts (12, 34) associated with lowered levels in well-being and productivity or lowered academic achievement amongst young people (31, 60–63) due to excessive social media and smartphone use (64–66), these constant disruptions may be associated with hyperactivity levels (67), negative affect, sensitivity to evaluation, poor emotion regulation, and problematic smartphone use (68–74). Attempting to achieve relief from negative emotions elicited smartphone use is reinforced (75, 76), leading to poor metacognition (77). However, despite accruing evidence for emotional and behavioral consequences of problematic smartphone use, the processes leading to addictive use (78) remain conceptually unclear and methodologically questionable partially due to the constantly evolving nature of products and services (17, 79–82) alongside the wide range of contents (social, information) smartphones provide access to.

Research on distraction and its association with problematic smartphone use is still scarce and there are no available psychometric assessment tools within the smartphone and social media literature to assess this cognitive and emotive process parsimoniously. Subscales within attention scales, executive function scales, and problematic internet use scales partially assess the role of distraction as a cognitive mechanism occurring in the digital environment (83–85). However, many of the existing psychometric scales are limited to a few items only, and therefore are neither comprehensive nor representative of the complexity involved in smartphone use experience, frequent attentional loss, and the associated processes experienced by smartphone users (i.e., urge to check, cue reactivity). Given that frequent attentional loss has been reported to affect executive function areas, critical for paying attention, decision-making, planning, organization, higher-order thinking, and regulating emotions (86, 87), it is important to assess distraction within the smartphone context with accuracy. Thus, the psychological function of distraction in the online environment should be further scrutinized since distraction is not a unitary process, but rather a multidimensional construct associated with both adaptive and maladaptive functions, rendering the development of such psychometric test timely due to the need to further understand this phenomenon and its relationship to problematic smartphone use as a psychological experience.

Smartphone distraction among young people primarily occurs due to social media content. Smartphone use and social media use are inextricably interwoven for young people due to the prominent social element in smartphone use (88) leading to distraction and academic work conflict (89). More specifically, the rationale for the development of this scale was based on the premise that distractive smartphone use appears to be driven primarily by the cognitive preoccupation with social media content in order to attend to needs for validation and control (of content, self-presentation, and relationships). This preoccupation and urge to check (90) or interact, in turn, prompts emotional reactivity and behavioral activation in the form of distraction (40, 91), amplified by FOMO and the need to control self-presentation and others' perceptions or seek reassurance (92). This process could also be experienced from non-social use (73, 93) because smartphones are multi-purpose devices and recent studies suggest that process use (e.g., watching videos, browsing online) is widespread as much as social use (73) and with stronger associations with problematic smartphone use (92, 94). In the present study, it is contended (and supported by empirical studies) that social media content is largely responsible for the attentional drift associated with frequent and prolonged smartphone engagement among young adults (95, 96). A smartphone is therefore viewed as the medium providing access to the desired content reflecting the attachment formed to the device among young adults (97–103) and intensified by experiences of nomophobia (NOMO; the fear of being without a smartphone) (104–107) and FOMO (29, 108, 109). However, the assessment of the relative role of process smartphone use and its relationship to smartphone distraction requires further exploration. Given the increasing mobile connectivity, providing access to social media via smartphones (110), and the frequent engagement with social content by emergent adults (111, 112), the use of social media measures (metacognitions and problematic social media use) were deemed appropriate to support the validity of the new measure.

Prior studies have confirmed gender differences in emotional distraction and reactivity (145). Within smartphone use, emergent evidence has also demonstrated gender-based differences with empirical studies to date presenting with mixed results concerning gender differences in smartphone use (124, 146–154). Gender has also been arguably identified as a potential risk factor for the development of problematic smartphone use with more females reporting higher problematic smartphone use than males but also gender differences in social media and other smartphone-related behaviors (155–157). However, given the novelty of the construct, gender differences have not been examined in relation to smartphone distraction. Therefore, a multiple group confirmatory factor analysis was undertaken to assess measurement invariance (configural, metric, and scalar) of the Smartphone Distraction Scale (SDS) across gender, and investigate gender-related latent mean differences across all the identified latent factors. Based on the analysis of the current literature, higher scores for smartphone distraction were expected for females than for males.

The present study therefore aimed to develop and empirically validate a psychometric scale to assess smartphone distraction (SD), the SDS. This was developed to identify its latent dimensions while accounting for the smartphone context, the extant empirical evidence, and the theoretically-relevant frameworks suggested (52, 58). More specifically, the present study aimed to fulfill the following primary objectives: (i) examine the factorial validity and reliability of the SDS using exploratory and confirmatory factor analysis, and (ii) investigate the convergent and divergent validity by examining the relationship between the SDS and problematic social media use, metacognition, mindful attention, stress and smartphone-related psychological constructs. To achieve the aforementioned objectives, it was hypothesized that: (i) the SDS would show robust psychometric properties; and (ii) those with higher levels of distraction would present higher scores of problematic social media use, stress, and other relevant psychological constructs (i.e., self-regulation). It is envisaged by the present authors that the development and psychometric validation of a scale for SD will contribute to its assessment in academic institutions and work-related environments, generating further multidisciplinary scientific knowledge about this disruptive construct and its relationship with mental health correlates in smartphone use.

Attention is a scarce resource and fragmented attention appears to be a frequent outcome of smartphone use related to cognitive interference and interruptions (48, 235, 236). Distraction is one expression of attentional loss associated with smartphone use. The present study explored a newly conceptualized, theory-guided, multidimensional measure of SD based on the need to understand and develop a psychometric assessment framework for SD. To achieve this goal, the perceptual control theory (58) and the control model of engagement for social media and smartphone use (52) among young adults were adopted to explain the tendency for distraction in order to control self-presentation, content and relationships online. The present study had the following aims: (i) identify the latent dimensions of SD and develop a respective pool of items, (ii) evaluate the scale's validity and reliability, (iii) investigate the criterion-related, convergent, and divergent validity with existing measures from the smartphone literature, and (iv) establish gender invariance (at the configural, metric, and scalar levels), and test latent mean differences across males and females. The SDS appeared to be a valid and reliable measure for the assessment of SD with sound psychometric properties and invariance across gender among young adults. Results from the measurement invariance analysis supported the configural, scalar, and metric invariance for the four-factor structure, suggesting that the SDS is comparable across the two groups. Furthermore, latent mean differences indicated that females were more susceptible to SD than males, consistent with the smartphone literature (148, 154, 208).

The analyses conducted provided evidence of the validity of a four-factor structure comprising of attention impulsiveness, emotion regulation, online vigilance, and multitasking and confirming that SD entails a cognitive, emotive, and behavioral component, consistent with the evidence reported in the literature (8, 27, 56, 60, 120, 237, 238). Statistically, the four-factor model was followed with a marginal difference in terms of fit by a hierarchical model, providing further evidence of the multidimensional and multifaceted nature of SD rendering a second-order model (239). However, the more parsimonious solution was chosen as suggested by scholars (240). In the four factor model, as hypothesized, the first factor (Emotion Regulation) was the strongest factor referring to strategies individuals use to modulate the emotional state they are in, the timing of the emotion and its expression (241), suggesting that SD has a strong regulating function consistent with literature (242–246). Emotion regulation has been found to be associated with self-control and can be dependent on intrinsic (i.e., temperamental) or extrinsic (i.e., attachment) factors (247) and may be regulated through avoidance, suppression, or enforced expression or reappraisal (241). Within smartphone use, distraction appears to serve a protective function by re-directing attention to a situation of less valence avoiding negative emotional states, consistent with evidence of general distraction and interference in anxiety (248, 249). However, overreliance may be associated with problematic smartphone and social media use (83).

The second factor (Attention Impulsiveness) referred to difficulties in the regulation of attention and engagement in impulsive behavior. Impulsivity has been linked to temporal discounting of rewards driven by emotion regulation and presenting as reaction to emotional arousal (250). Distraction frequency has been associated with attention impulsiveness, which is triggered by anxiety and takes the form of attentional bias (23), as has been supported in the smartphone and social media use literature (101, 249, 251). Attention impulsiveness has also been associated with habitual checking (121), chronic media multitasking and attention decrements (12) as well as with impaired disengagement in Internet Gaming Disorder (IGD) (252). In conditions where learning is of low interest, attentional impulsivity is associated with increased interruptions, reduced lecture comprehension, low motivation, and fluid intelligence (35, 36), to the detriment of academic performance and tasks requiring sustained attention (37).

The third Factor (Online Vigilance) related to cognitive preoccupation and orientation toward social media content with items reflecting salience (i.e., thinking intensively online spaces), reactivity (i.e., readiness to react to smartphone cues even if it involves interruption of activities), and monitoring (i.e., tendency to actively observe online engagement parallel to other activities) (91). The findings supported a strong relationship between distraction and online preoccupation and vigilance, and may predispose an individual to distract frequently and check digital devices excessively for reassurance (92) and use smartphones more than intended or in a compulsive way (52, 91, 253). Online vigilance therefore, appears potentially fueled by FOMO and associated with disruptions to attend to smartphone content, further corroborating previous findings from the literature reporting regulation deficits in IGD and Problematic Internet Use (PIU) (118, 186, 254, 255). Strong habitual checking behaviors, reinforced by the immediate smartphone access to social media and the disruption of notifications, appear to be leading to self-control failures (125).

The fourth Factor (Multitasking) represented general multitasking behavior taking place while using smartphones, which may be associated with a distractive state (237). Task switching requires time investment and mental resources to re-orient to the task at hand with responses being slower and more error-prone (256). Multitasking has been considered as functionally equivalent to distraction (237). However, multitasking may mask the perception of distraction (257). There are reasons to expect a high degree of overlap among the four dimensions, reflected in the high co-variances amongst the factors as well as in the error terms of specific items. All dimensions measured distraction within smartphone use and had an implicit or explicit focus on cognitive preoccupation with smartphone content (primarily social media content, for emotion regulation and resulting attention loss, potentially leading to checking and multitasking), in accordance with evidence (12, 23, 24, 237, 258–260). Therefore, the overlap and the high inter-correlation amongst the factors was expected. However, recent evidence on highly prevalent non-social smartphone and process use (e.g., watching videos, browsing online) (73) has been associated with problematic smartphone use (92, 94) and should therefore be taken into account in future studies by including items related to the diverse content that a smartphone provides access to.

To establish the convergent and discriminant validity of the SDS, the study investigated the association between various cognitive, emotional, and behavioral variables and the SDS factors. Criterion-related and convergent validity was demonstrated through associations with daily smartphone and social media use, attentional control and mindful attention and awareness. Significant correlations were also observed between the four factors of the SDS and corresponding psychological constructs, such as deficits in emotion regulation, problematic social media use, and poor metacognition, thus providing further evidence for the test's convergent validity and bridging research on IGD and PIU with social media and smartphone use in identifying common risk factors and potential outcomes (118, 186, 254, 255, 261, 262). Therefore, the SDS appears to demonstrate acceptable validity and reliability.

Additionally, the present study aimed to assess measurement invariance of the SDS across gender. The findings obtained suggested that the SDS factor structure is the same across gender with equally robust associations between the underlying constructs and the observed indicators across genders, thus providing additional support for the four-factor structure of the SDS. In addition, the SDS achieved both metric and scalar invariance, suggesting equal salience of the indicators across the two groups, providing additional evidence of construct validity for cross-group comparisons for the SDS. As suggested in previous literature, measurement invariance needs to be supported before any cross-cultural investigations of the scale are attempted (231). Although the SDS demonstrated measurement invariance, findings suggested that the latent means for the SDS subscales differed across gender groups. Latent mean differences were assessed by using a latent modeling approach which is considered a more robust approach (when compared to testing mean differences with t-tests), providing strong empirical support for gender differences (212). The results from this analysis found that students of both genders were not similar in their endorsement of the SDS subscales, with females exhibiting higher scores than males across all subfactors, contributing to the emerging body of smartphone literature on gender (146, 147, 154).

These results are also in line with findings from previous studies in which females appear to demonstrate higher multitasking and emotion regulation needs, and to manage their emotions more poorly than males and present with higher problematic smartphone use (146, 152, 263–266). Evidence regarding gender differences in multitasking is inconclusive due to conflicting findings, with some evidence suggesting that women are not better than men at multitasking, while other literature suggests that women present with better multitasking skills (151, 267). To explain these differences, the hunter-gatherer hypothesis (claiming a cognitive adaptation to different division of labor roles across the sexes) (268) has been proposed to explain findings of females being less affected by task-irrelevant interruptions in experimentally-generated multitasking conditions, suggesting that females are better at multitasking. However, media multitasking is considered the new norm, and inadvertently leads to fragmented attention and frequent micro-disengagements due to interruptions (39), linking multitasking with distraction (269). Still, no direct conclusions may be drawn given the relative absence of research on SD to date. Previous studies examining differences between genders in smartphone use have indicated that females report higher smartphone use and present with greater prevalence of problematic smartphone use (147, 148, 270), which clearly indicates cross-gender differences (271).

To the best of the authors' knowledge, the present study is the first to develop and investigate the psychometric properties of a newly developed measure on SD, as well as to provide evidence regarding measurement invariance across gender. The findings of this study suggest that the SDS functions well and is invariant across genders among young people, providing new insights in the smartphone literature by suggesting cognitive and emotive effects in terms of attentional loss from smartphone use across genders. The SDS presents with a strong theoretical foundation, good psychometric properties, short length, and easy applicability. The findings obtained suggest that the instrument may be used and further tested in the general population when assessing the construct of SD.

The SDS requires further investigation with ethnically diverse samples and different age groups and settings, establishing its test-retest stability, invariance across different cultures, and its predictive validity, by exploring its relationship with other relevant psychological constructs, such as anxiety and mood disorders or attention deficit hyperactivity disorder (ADHD) (272), especially in clinical samples by identifying how the frequency and compulsiveness of smartphone use and the impact of this cognitive-emotive construct may contribute to the deterioration or alleviation of symptoms of various disorders (273). Additionally, the role of SD should be examined in terms of risky behaviors, physical injuries (17, 274), work performance so that greater knowledge about SD may be generated within distinct subgroups and environments. Associations of SD with metacognition for problematic smartphone use should be further explored with the use of validated instruments (116), as no relevant measure was available during data collection of the present study. Therefore, further validation of the construct is required and to encourage research investigating distraction in other contexts.

Potential limitations in the present study include the lack of specific aspects of internal consistency of the scale such as test-retest reliability and its limited generalizability to the broader population, having relied on a convenience self-selected sample of university students, which may not necessarily be representative of all smartphone users. It is unclear how culturally distinct or age different samples (e.g., young children) might respond to this scale. Additionally, the content of the items may warrant further refinement (i.e., the driving item was not relevant among emergent adults). However, SD has been suggested as a common behavior of concurrent smartphone use among older adults (17). Another important potential limitation constitutes the use of self-report questionnaires and potential biases associated with self-report methods (e.g., social desirability, memory recall). Combined with behavioral and biometric data, psychometric measures of SD as both an adaptive but also as a maladaptive digital experience could provide strong evidence of face validity. Additionally, the construct of SD does not encompass other experiences of distraction on other digital devices or media multitasking or process smartphone use. Smartphones were chosen because they are the most ubiquitous and pervasive devices. Such insight would make it possible to discern whether the nature of distraction similarly to online addiction varies between platforms, digital devices, and content types (275). Future studies may consider including items related to media multitasking and overall digital distraction arising from using multiple devices may provide a more inclusive account of the digital experience. The present study and its findings support the use of the SDS four factor model. However, the present study did not test equivalence for the hierarchical model. Still, the adequate fit of the hierarchical model, which was marginally inferior to the first order, suggests a strong general factor representing the construct of smartphone distraction. Thus, when calculating scores, authors are advised to work with subscale scores or use a total score. However, given that the the hierarchical model was not tested for invariance in this preliminary investigation, which focused primarily on the development and initial validation of the scale, invariance testing of the second order model and latent mean differences is strongly recommended to be tested in a future study to support equivalence across genders and assess gender differences in the hierarchical model. The first step of invariance in the four factor model, which is a prerequisite to testing invariance of the hierarchical model has been satisfied in the present investigation.

The findings obtained suggest that the SDS is a psychometrically sound scale assessing SD guided by two theoretical frameworks according to which cognitive preoccupation and need to control content, relationships, and self-presentation appear to be key drivers for distraction via smartphone use. The SDS was designed to be applicable to young adult smartphone users irrespective of level of smartphone use, whether excessive or judicious. The SDS may be utilized as a screening tool in interventions to reduce the risk of problematic smartphone use in student populations (276). Given that smartphones are ubiquitous, SD is a common behavior, impacting productivity and areas of executive function (277), and therefore reducing distraction may be of particular importance to aid and enhance performance, emotion regulation, and overall psychological well-being.

Attention management may be one of the most critical skills of this century where information is abundant. Attention is a scarce resource and its control may be impaired by the online environment and digital devices available. Distraction is invariably part of an individuals' online and offline experiences. The present study sought to devise the first SDS and further investigate its psychometric properties, given the absence of a similar construct in the smartphone literature. The SDS is best conceptualized within a four-factor solution. Additionally, the SDS was found to present with gender measurement invariance at the configural, metric, and scalar levels, suggesting that the scale functions equivalently across the two gender groups. Moreover, latent mean analysis indicated gender differences underlying both cognitive and emotive dimensions of distraction in smartphone use. The SDS is a theory-guided scale, with sound psychometric properties assessing a complex psychosocial construct defined by cognitive-emotive dimensions with positive and negative valence related to attention impulsiveness, emotion regulation, online vigilance, and multitasking. Within the smartphone literature, SD is an emergent issue interfering with everyday functioning and productivity and potentially implicated in problematic smartphone and social media use.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Nottingham Trent University College of Business, Law and Social Sciences. The patients/participants provided their written informed consent to participate in this study.

MT: principal investigator, main author, study design, data collection, and statistical processing of the data. HP and IT: statistical and methodological supervision. MG, MR, DK, and HP: supporting the study design and supervision of the study. MT, HP, IT, MG, MR, and DK: editing the manuscript. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.