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Digital Daydreaming: Introducing the Spontaneous Smartphone Checking Scale

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Title: Digital Daydreaming: Introducing the Spontaneous Smartphone Checking Scale
Language: English
Authors: Berntsen, Dorthe (ORCID 0000-0001-5941-314X), Hoyle, Rick H., Munkholm Møller, Daniel, Rubin, David C.
Source: Applied Cognitive Psychology. Jan-Feb 2023 37(1):147-160.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 14
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Descriptors: Handheld Devices, Telecommunications, Measures (Individuals), Attention, Validity, Psychometrics, Behavior, Cognitive Processes
DOI: 10.1002/acp.4034
ISSN: 0888-4080
1099-0720
Abstract: Smartphones are a ubiquitous part of many people's lives, but little is known about their impact on everyday thought processes. Here we introduce the "spontaneous smartphone checking scale" (SSCS)--which measures the tendency to direct attention toward one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goal in mind, as a parallel to mind-wandering directed toward internal thoughts. The SSCS showed good psychometric properties and construct validity. It separated from measures of daydreaming and mind-wandering by not loading on dimensions related to self-consciousness, reflection, and rumination, but instead loading highly on a factor associated with other aspects of digital communication and concerns about public appearance on social media. This suggests that spontaneous smartphone checking serves different mental and social functions than internally generated spontaneous thought processes. We discuss possible long-term effects of spontaneous smartphone checking taking up time for internally generated spontaneous thoughts.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1363094
Database: ERIC
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  Value: <anid>AN0161473728;bu801jan.23;2023Jan27.04:20;v2.2.500</anid> <title id="AN0161473728-1">Digital daydreaming: Introducing the spontaneous smartphone checking scale </title> <p>Smartphones are a ubiquitous part of many people's lives, but little is known about their impact on everyday thought processes. Here we introduce the spontaneous smartphone checking scale (SSCS)—which measures the tendency to direct attention toward one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goal in mind, as a parallel to mind‐wandering directed toward internal thoughts. The SSCS showed good psychometric properties and construct validity. It separated from measures of daydreaming and mind‐wandering by not loading on dimensions related to self‐consciousness, reflection, and rumination, but instead loading highly on a factor associated with other aspects of digital communication and concerns about public appearance on social media. This suggests that spontaneous smartphone checking serves different mental and social functions than internally generated spontaneous thought processes. We discuss possible long‐term effects of spontaneous smartphone checking taking up time for internally generated spontaneous thoughts.</p> <p>Keywords: daydreaming; habit; mind‐wandering; self‐consciousness; smartphone; spontaneous thought</p> <hd id="AN0161473728-2">INTRODUCTION</hd> <p>Your smartphone has not notified you in any way, yet you reach for it and check it. Why? Maybe you were bored. Maybe you had a minute or two to spend while waiting for someone. Maybe you were walking your dog or having an uninteresting conversation.</p> <p>For most people, the phone is always there as a source of entertainment, information, and distraction. In the United States, more than 80% of the population owns a smartphone. Comparable prevalences are found in other advanced economies. In emerging economies, numbers are lower, but rising (Pew Research Center, [<reflink idref="bib34" id="ref1">34</reflink>]). Given the fact that the first smartphone was launched in 2007, smartphones appear to have been adopted faster than any other technology in history (Kushlev, Dwyer, & Dunn, [<reflink idref="bib26" id="ref2">26</reflink>]).</p> <p>This new technology has brought many advantages, but several psychological drawbacks have also been pointed out. The ubiquitous use of smartphones with expectations of instantaneous communication through text messages and social media may interfere with everyday social interactions (Sbarra et al., [<reflink idref="bib38" id="ref3">38</reflink>]), creating situations with "absent presence" in which the person is physically present but mentally occupied by a mediated world elsewhere (Gergen, [<reflink idref="bib17" id="ref4">17</reflink>]). Research has shown that having a smartphone physically present reduces satisfaction with face‐to‐face interactions (Dwyer et al., [<reflink idref="bib13" id="ref5">13</reflink>]), and that people who have their smartphone available are less inclined to display approach behavior toward strangers (Kushlev, Hunter, et al., [<reflink idref="bib27" id="ref6">27</reflink>]). There is also evidence that the mere presence of a smartphone during a cognitive task lowers performance (Ward et al., [<reflink idref="bib53" id="ref7">53</reflink>]). Finally, researchers have suggested that excessive smartphone usage qualifies as a form of addictive behavior (see Harris et al., [<reflink idref="bib19" id="ref8">19</reflink>], for a review).</p> <p>Here we pursue a different issue: Until the early 2000s, before the smartphone had become something most people own, people typically looked into the air, seemingly contemplating their own inner life during waiting time and other non‐demanding moments. Now the large majority appears to look at their phone (Kruger et al., [<reflink idref="bib25" id="ref9">25</reflink>]). This is a major change in how people spend non‐demanding moments in everyday life. To probe individual differences in the tendency to engage in such activity, we here introduce the <emph>spontaneous smartphone checking scale</emph> (SSCS) and examine how the tendency to spontaneously check one's smartphone relates to other individual differences. We propose the idea that spontaneous smartphone checking may replace daydreaming and mind wandering directed toward the inner life of the person, and we explore possible consequences of such replacement for other mental functions such as self‐consciousness and reflection.</p> <p>We define spontaneous smartphone checking as the direction of attention toward the phone that is unpreceded by external prompts (e.g., notifications, or alerts) and happens with no specific conscious goal in mind. Spontaneous smartphone checking can be seen as an instance of what Wilmer et al. ([<reflink idref="bib54" id="ref10">54</reflink>]) termed, endogenous interruptions, which occur "when the user's own thoughts drift toward a smartphone‐related activity, and thereby evince an otherwise unsolicited drive to begin interacting with the device" (p. 4). This is in contrast with exogenous interruptions typically in response to an alert coming from the phone itself (Wilmer et al., [<reflink idref="bib54" id="ref11">54</reflink>]).</p> <hd id="AN0161473728-3">Functional similarities between spontaneous smartphone checking and daydreaming</hd> <p>We use the term spontaneous smartphone checking as an analogue to the notion of spontaneous thought. Spontaneous thought is an umbrella term for thoughts that are unplanned and occur without being directed at an immediate goal in the ongoing situation. It encompasses such notions as mind‐wandering and daydreaming (Fox & Christof, [<reflink idref="bib15" id="ref12">15</reflink>]). Different types of spontaneous thought have been identified, and distinctions still need to be clarified (Seli et al., [<reflink idref="bib40" id="ref13">40</reflink>]).</p> <p>Several functional similarities support the idea that engaging in spontaneous smartphone checking may partially replace spontaneous thought directed toward one's inner life by taking up time slots that otherwise would be used for the latter. First, there is substantial evidence that the likelihood of engaging in daydreaming and mind wandering increases with reduced attentional demands of the ongoing situation (Singer, [<reflink idref="bib43" id="ref14">43</reflink>]; Smallwood & Schooler, [<reflink idref="bib47" id="ref15">47</reflink>]). In everyday life, people are more likely to engage in mind‐wandering if they are not focused on a task and if the current task is perceived as boring and undesirable (Kane et al., [<reflink idref="bib21" id="ref16">21</reflink>]). Daydreaming has been conceived as a baseline state to which the mind reverts in the absence of tasks that require focused and sustained attention (Klinger, [<reflink idref="bib23" id="ref17">23</reflink>]; Klinger et al., [<reflink idref="bib24" id="ref18">24</reflink>]). Although studies are lacking, the same appears to characterize the tendency to spontaneously check one's phone. For example, cell phone usage is rapidly initiated when entering waiting spaces, such as waiting in a line in a coffee shop or restaurant (Kruger et al., [<reflink idref="bib25" id="ref19">25</reflink>]). Thus, both types of activities appear to take place during non‐demanding moments or when failing to attend to a task, and therefore can be seen as competing for attention during such moments.</p> <p>Second, both activities are largely context‐independent. There are few contextual constraints on engaging in daydreaming and mind wandering. An internal stream of thought is carried along with us wherever we go as a possible source of distraction and enrichment (e.g., Singer, [<reflink idref="bib42" id="ref20">42</reflink>], [<reflink idref="bib43" id="ref21">43</reflink>]). The same can be said about the phone in people's purse or pocket. Smartphones are small, portable devices with countless functions that can be used in almost any context. This underscores the ability of smartphones to replace spontaneous thoughts during non‐demanding situations. Third, both activities involve the straddling of two worlds (Bayer et al., [<reflink idref="bib5" id="ref22">5</reflink>]); that is, the external, physical world versus the inner world of thoughts in the case of daydreaming, and the physical versus the virtual world in the case of smartphone usage. Thus, both involve a partial decoupling from the immediate physical world, and both can thus serve to reduce boredom when the immediate physical surroundings provide little stimulation.</p> <p>The two processes also share other functional features. Smartphone usage may happen automatically, in response to minimally conscious impulses, but may also reflect highly conscious processes and involve immersion and absorption (Bayer et al., [<reflink idref="bib5" id="ref23">5</reflink>]). Similarly, mind‐wandering may be initiated both unintentionally and intentionally (e.g., Seli, Risko, & Smilek, [<reflink idref="bib41" id="ref24">41</reflink>]). Often, unintentionally initiated mind‐wandering will be followed by more intentionally sustained thoughts involving active decoupling from the external environment (Smallwood, [<reflink idref="bib45" id="ref25">45</reflink>]). Both activities may also be seen as facilitated by cues. Spontaneous thoughts, such as involuntary autobiographical memories are often cued by aspects of the surroundings (Berntsen, [<reflink idref="bib7" id="ref26">7</reflink>]). Similarly, the mere presence of one's phone may prompt spontaneous smartphone checking. Finally, both activities create situations characterized by divided attention that often is detrimental to the ongoing task, such as during driving (Berthié et al., [<reflink idref="bib9" id="ref27">9</reflink>]; García‐Herrero et al., [<reflink idref="bib16" id="ref28">16</reflink>]; Strayer et al., [<reflink idref="bib49" id="ref29">49</reflink>]; see Ralph et al., [<reflink idref="bib36" id="ref30">36</reflink>], for further discussion on parallels between mind‐wandering and multimedia usage).</p> <p>In spite of these similarities, important differences exist. When people daydream, they direct attention toward their own personal thoughts and their personally remembered past and imagined future. In contrast, when people spontaneously check their phone, their attention is typically directed toward a virtual world that to a large extent is shaped by others, and constrained by the program (or app) they are using rather than by their own mental abilities and concerns. If mind‐wandering serves to support goal pursuit, future planning, and creativity, as often suggested (e.g., Klinger, [<reflink idref="bib23" id="ref31">23</reflink>]; Klinger et al., [<reflink idref="bib24" id="ref32">24</reflink>]; Smallwood & Schooler, [<reflink idref="bib48" id="ref33">48</reflink>]), then it may be detrimental to well‐being if smartphone usage to a large extent fills the relatively limited time slots everyday life holds for such unconstrained thoughts and contemplation. On the other hand, engaging in smartphone checking may be a way of avoiding unwanted spontaneous thoughts, such as worry and rumination.</p> <hd id="AN0161473728-4">The present studies</hd> <p>The aim of the present series of studies is to introduce a measure of individual differences in the frequency of spontaneous smartphone checking and to examine how this tendency relates to other individual differences. Our aim is not to introduce a new scale for problematic or pathological mobile phone usage, because such measures already are well‐represented in the literature, amounting to 78 different validated scales introduced over the last 13 years according to a recent review (Harris et al., [<reflink idref="bib19" id="ref34">19</reflink>]). Instead, we aim to introduce a scale that simply measures the propensity to spontaneously check one's phone, conceived as a trait‐like disposition or habit and neutral with regard to pathology and negative affect. We contrast this measure with a representative set of the numerous measures of smartphone addiction, and situate our measure in the conceptual space of spontaneous thought, self‐consciousness, and problematic smartphone usage.</p> <p>Study 1 introduces the SSCS and explores its psychometric properties as well as its relation to measures of smartphone addiction, depression, self‐consciousness and spontaneous thoughts. Study 2 replicates and extends Study 1 with the nine items included in the final SSCS. Together Studies 1 and 2 demonstrate sound psychometric qualities of the SSCS and establish it as a measure of non‐pathological behavior. Study 3 further explores its associations with tendencies to engage in internally generated thoughts and other measures of digital media usage.</p> <hd id="AN0161473728-5">STUDY 1</hd> <p></p> <hd id="AN0161473728-6">Method</hd> <p></p> <hd id="AN0161473728-7">Participants</hd> <p>We recruited 209 participants from Amazon Mechanical Turk using CloudResearch (Litman et al., [<reflink idref="bib31" id="ref35">31</reflink>]); 87 women and 122 men with a mean age of 35.19 years (SD = 10.64), range 19–69 years of age. To be included in the study, the participants had to give informed consent, be native English speakers, own a smartphone, pass three attention checks, and provide meaningful answers to an open‐ended question (i.e., not copy and paste from websites or provide inadequate responses).[<reflink idref="bib1" id="ref36">1</reflink>] Each worker was paid 2 USD.</p> <p>Here and in the following studies, all Danish ethical codes, laws, and regulations for research involving humans were followed, and the work was conducted in accordance with international, professional ethical guidelines and recommendations by the local ethics committee.</p> <hd id="AN0161473728-8">Scale development</hd> <p>Table 1 shows the final version of the SSCS. We intended the SSCS to probe spontaneous smartphone checking, that is, unprompted checking of the phone. Therefore, we employed the following prefix for all questions "My smartphone has not notified me in any way, but I still check it ...." Each item of the scale then described a possible context in daily life where a person might spontaneously check their phone with no prompts. Because our intention was to capture smartphone usage analogous with engaging in spontaneous thought, the individual items were generated based on research on individual differences in experiencing involuntary memories (Berntsen et al., [<reflink idref="bib8" id="ref37">8</reflink>]), mind‐wandering (Carriere et al., [<reflink idref="bib10" id="ref38">10</reflink>]), and our general intuition about smartphone checking. Specifically, three items described everyday contexts previously used in the involuntary autobiographical memory inventory (IAMI; Berntsen et al., [<reflink idref="bib8" id="ref39">8</reflink>]; items 1, 2, and 8 in Table 1). Three items addressed everyday contexts derived from the mind wandering and daydreaming literature (items 5, 6, and 7 in Table 1). Three items described common situations that almost everybody would be expected to experience on a regular basis, and which often involve little attentional demands (items 3, 4, and 9 in Table 1). It should be underscored that these criteria are not mutually exclusive and were used simply as a governing strategy for generating items addressing a broad range of everyday contexts that most people would be expected to encounter on a regular basis and that would be of relevance for the topic. The first version of the SSCS, which we administered to the participants in Study 1 consisted of 13 items; the nine items shown in Table 1 and four additional items that were excluded mainly for statistical reasons (see section 2.2.1).</p> <p>1 TABLE Spontaneous smartphone checking scale (SSCS)</p> <p> <ephtml> <table><tbody valign="top"><tr><td>Instructions:The following questions address how often you spontaneously check your smartphone, without planning to do so at the moment. The checking happens in situations without phone notifications and with no clear goal or task in mind. For each question, please use the response option (from 1 'never' to 7 'extremely often') that best fits your experience of the frequency.My smartphone has not notified me in any way, but I still check it...<list list-type="Bullet"><list-item><p>When I am relaxing or doing routine work</p></list-item><list-item><p>When I experience some emotions, moods, or thoughts</p></list-item><list-item><p>In social situations</p></list-item><list-item><p>When I am outside</p></list-item><list-item><p>When I have a vacant moment</p></list-item><list-item><p>During ongoing tasks</p></list-item><list-item><p>When I am in a line</p></list-item><list-item><p>When I am listening to music</p></list-item><list-item><p>When I am watching TV</p></list-item></list>Rating Scale1 = Never; 7 = Extremely often<xref ref-type="fn" rid="tfn1" /></td></tr></tbody></table> </ephtml> </p> <p>1 1 The copyright for the SSCS is held by the authors (© 2023, Berntsen, Hoyle, Møller & Rubin). Permission is given to use the scale for research purposes.</p> <hd id="AN0161473728-9">Material</hd> <p>In addition to the SSCS, we included a number of other scales intended to explore the construct validity and psychological correlates of the SSCS. See Table 2 for descriptive statistics and reliability measures.</p> <p>2 TABLE Descriptive statistics for Study 1 (N  = 209), Study 2 (N  = 256) and Study 3 (N  = 202)</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Scales</th><th align="left">Study 1</th><th align="left">Study 2</th><th align="left">Study 3</th></tr><tr><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left"><italic>α</italic></th><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left"><italic>α</italic></th><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left"><italic>α</italic></th></tr></thead><tbody valign="top"><tr><td>SSCS</td><td>37.34</td><td>11.93</td><td>.89</td><td>39.27</td><td>11.26</td><td>.88</td><td>38.58</td><td>10.90</td><td>.87</td></tr><tr><td>SAS‐SV</td><td>25.09</td><td>10.60</td><td>.89</td><td>26.48</td><td>11.68</td><td>.92</td><td>25.51</td><td>11.32</td><td>.92</td></tr><tr><td>CES D</td><td>24.97</td><td>10.67</td><td>.86</td><td>24.42</td><td>10.69</td><td>.87</td><td>–</td><td>–</td><td>–</td></tr><tr><td>MW‐D</td><td>4.42</td><td>01.51</td><td>.90</td><td>4.60</td><td>1.42</td><td>.90</td><td>4.49</td><td>1.47</td><td>.91</td></tr><tr><td>MW‐S</td><td>4.02</td><td>1.42</td><td>.83</td><td>4.10</td><td>1.48</td><td>.86</td><td>4.14</td><td>1.37</td><td>.85</td></tr><tr><td>IAMI<sup>1</sup></td><td>1.82</td><td>.80</td><td>.95</td><td>1.78</td><td>.80</td><td>.96</td><td>–</td><td>–</td><td>–</td></tr><tr><td>SCS‐R PRI</td><td>15.09</td><td>5.18</td><td>.78</td><td>15.18</td><td>5.21</td><td>.78</td><td>15.39</td><td>5.20</td><td>.81</td></tr><tr><td>SCS‐R PUB</td><td>11.22</td><td>4.79</td><td>.82</td><td>11.38</td><td>5.01</td><td>.86</td><td>12.03</td><td>4.90</td><td>.86</td></tr><tr><td>SCS‐R SOC</td><td>10.35</td><td>4.85</td><td>.85</td><td>9.47</td><td>5.00</td><td>.86</td><td>10.10</td><td>4.95</td><td>.85</td></tr><tr><td>BSSS</td><td>2.78</td><td>.83</td><td>.82</td><td>2.74</td><td>.86</td><td>.84</td><td>–</td><td>–</td><td>–</td></tr><tr><td>SPR</td><td /><td /><td /><td>21.57</td><td>5.62</td><td>.80</td><td>20.90</td><td>5.47</td><td>.79</td></tr><tr><td>MSU ESC</td><td /><td /><td /><td>8.95</td><td>3.67</td><td>.89</td><td>–</td><td>–</td><td>–</td></tr><tr><td>MSU ENT</td><td /><td /><td /><td>19.73</td><td>3.92</td><td>.88</td><td>–</td><td>–</td><td>–</td></tr><tr><td>DDFS</td><td /><td /><td /><td /><td /><td /><td>32.49</td><td>10.79</td><td>.95</td></tr><tr><td>RRQ‐RUM</td><td /><td /><td /><td /><td /><td /><td>39.26</td><td>11.11</td><td>.94</td></tr><tr><td>RRQ–REF</td><td /><td /><td /><td /><td /><td /><td>40.32</td><td>10.30</td><td>.93</td></tr><tr><td>PrSA</td><td /><td /><td /><td /><td /><td /><td>18.13</td><td>6.96</td><td>.89</td></tr><tr><td>PubSA</td><td /><td /><td /><td /><td /><td /><td>23.50</td><td>9.19</td><td>.93</td></tr><tr><td>ASMR</td><td /><td /><td /><td /><td /><td /><td>3.03</td><td>1.49</td><td>.95</td></tr></tbody></table> </ephtml> </p> <ulist> <item>2 <sups>1</sups><emph>N</emph> = 202 in Study 1.</item> <item>3 Abbreviations: ASMC, the appearance‐related social media consciousness scale; BSSS, brief sensations seeking scale; CES‐D, center for epidemiologic studies depression scale; DDFS, daydreaming frequency scale; IAMI, involuntary autobiographical memory inventory; MSU, motivation for smartphone use: Escapism and entertainment subscales; MW‐D, mind‐wandering deliberate scale; MW‐S, mind‐wandering spontaneous scale; PrSA, private self‐absorption; PubSA, public self‐absorption; RRQ‐RUM, the rumination and reflection questionnaire, reflection subscale; RRQ‐RUM, the rumination and reflection questionnaire, rumination subscale; SAS‐SV, smartphone addiction scale—Short version; SCS‐R, self‐consciousness scale—Revised version: Private, public and social anxiety subscales; SPR, smartphone reliance test; SSCS, spontaneous smartphone checking.</item> </ulist> <hd id="AN0161473728-10">Smartphone addiction scale—Short version</hd> <p>This scale is a short version of the smartphone addiction scale (SAS‐SV) (Kwon, Lee, et al., [<reflink idref="bib28" id="ref40">28</reflink>]), which includes 10 items probing aspects of smartphone addiction, such as "missing planned work due to smartphone use." Each item is rated on a 6‐point scale (1–6) addressing levels of agreement. The sum score ranges from 10 to 60 (Kwon, Kim, et al., [<reflink idref="bib29" id="ref41">29</reflink>]).</p> <hd id="AN0161473728-11">The center for epidemiologic studies depression scale</hd> <p>The center for epidemiologic studies depression scale (CES‐D) is a 20‐item self‐report scale designed to assess symptoms of depression in the general population. The items of the scale describe well‐established symptoms associated with depression and the participant is asked to rate how frequently this has happened within the last week, for example, "I was bothered by things that usually don't bother me." Each item is rated on a 4‐point scale (0–3) addressing how frequently the symptom was experienced over the last week. Sum scores range from 0 to 60 (Radloff, [<reflink idref="bib35" id="ref42">35</reflink>]).</p> <hd id="AN0161473728-12">Deliberate and spontaneous mind‐wandering</hd> <p>The two scales probe the tendency to experience intentional/deliberate mind‐wandering (MW‐D) (e.g., "I allow my mind to wander on purpose") and the tendency to experience unintentional/spontaneous mind‐wandering (MW‐S) (e.g., "I find my mind‐wandering spontaneously"). Each scale includes four items rated on a 7‐point scale (1 = <emph>rarely</emph>, 7 = <emph>a lot</emph>), which are averaged to produce total scores (Carriere et al., [<reflink idref="bib10" id="ref43">10</reflink>]).</p> <hd id="AN0161473728-13">Involuntary autobiographical memory inventory</hd> <p>The IAMI consists of 20 items assessing the everyday frequency of having involuntary autobiographical memories and involuntary imaginations of future events. Specifically, 10 items assess the frequency of involuntary autobiographical memories (e.g., "Some locations or places bring memories of past events to mind—without me consciously trying to remember them"), and 10 items assess the frequency of involuntary future imagination (e.g., "Imaginary future events pop into my mind by themselves—without me consciously trying to evoke them"). The items are rated on a scale ranging from 0 (<emph>Never</emph>) to 4 (<emph>Once an hour or more</emph>). Ratings are averaged to produce a total score (Berntsen et al., [<reflink idref="bib8" id="ref44">8</reflink>]).</p> <hd id="AN0161473728-14">Self‐consciousness scale—Revised version</hd> <p>The self‐consciousness scale—Revised version (SCS‐R) consists of 22 items and three subscales: Private self‐consciousness (9 items, e.g., "I am always trying to figure myself out"), public self‐consciousness (7 items, e.g., "I am self‐conscious about the way I look") and social anxiety (6 items, e.g., "it takes me time to overcome my shyness in new situations"). Each item is rated from 0 to 3 ranging from <emph>not at all like me</emph> to <emph>a lot like me</emph> (Scheier & Carver, [<reflink idref="bib39" id="ref45">39</reflink>]). Subscale scores are produced by averaging ratings on the relevant items.</p> <hd id="AN0161473728-15">Brief sensation seeking scale</hd> <p>Brief sensation seeking scale (BSSS) probes sensation seeking based on eight items that pair into four highly correlated subscales: Experience seeking (e.g., "I would like to explore strange places"), boredom susceptibility (e.g., "I get restless when I spend too much time at home"), thrill and adventure seeking (e.g., "I like to do frightening things"), and disinhibition (e.g., "I like wild parties"). Responses are given on a 5‐point scale (1 = <emph>strongly disagree</emph> to 5 = <emph>strongly agree</emph>). We report the sum score, ranging 8–40 (Hoyle et al., [<reflink idref="bib20" id="ref46">20</reflink>]).</p> <hd id="AN0161473728-16">Procedure</hd> <p>A task was created and advertised in Amazon Mechanical Turk using CloudResearch (Litman et al., [<reflink idref="bib31" id="ref47">31</reflink>]). The advertisement briefly described the task, what was to be done, the approximate time that it might take, and the compensation that participants would receive if they completed the survey. We collected the data using the survey platform Qualtrics. Participants first gave informed consent and provided demographic information. They then answered the included scales in the following order: SSCS, BSSS, SCS, MW‐D and MW‐S, CES‐D, IAMI, and SAS. Participants also answered three attention checks that were included to ensure that they showed continuous attentiveness. Upon completion, participants were thanked for their participation and received a code to be provided in Amazon Mechanical Turk to receive payment.</p> <hd id="AN0161473728-17">Results</hd> <p>We present the results in the following order. We first describe the scale and item properties of the SSCS, especially how we reduced the original 13 item version of the scale to a 9 item version. We next describe how the nine item version correlates with other measures, with special attention to its relation to measures of smartphone addiction, spontaneous thought and depression.</p> <hd id="AN0161473728-18">Scale and item properties</hd> <p>We reduced the 13‐item scale to nine items based on the frequency distribution of responses to each item; that is, whether it was highly positively or negatively skewed, and/or showed weak correlations with other scale items. On this basis, we excluded four items[<reflink idref="bib2" id="ref48">2</reflink>]; two were negatively skewed, one was positively skewed, and one had a low interclass correlation (<.50). Excluding the four items reduced Cronbach's alpha from.90 to.89 and had minimal effects on the correlations with other measures. The final nine‐item version of the scale is presented in Table 1. Table 3 shows the statistics for each item. The following analyses are based on the nine‐item version.</p> <p>3 TABLE Item statistics for the spontaneous smartphone checking scale in Studies 1, 2, and 3</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Item</th><th align="left">Study 1</th><th align="left">Study 2</th><th align="left">Study 3</th></tr><tr><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left">Corrected item‐total correlation</th><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left">Corrected item‐total correlation</th><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left">Corrected item‐total correlation</th></tr></thead><tbody valign="top"><tr><td>1</td><td>4.62</td><td>1.68</td><td>.70</td><td>4.73</td><td>1.53</td><td>.71</td><td>4.73</td><td>1.62</td><td>.69</td></tr><tr><td>2</td><td>4.27</td><td>2.00</td><td>.64</td><td>4.41</td><td>1.85</td><td>.74</td><td>4.45</td><td>1.68</td><td>.66</td></tr><tr><td>3</td><td>3.88</td><td>1.85</td><td>.67</td><td>4.08</td><td>1.85</td><td>.61</td><td>3.99</td><td>1.78</td><td>.68</td></tr><tr><td>4</td><td>3.63</td><td>1.77</td><td>.65</td><td>3.74</td><td>1.79</td><td>.57</td><td>3.71</td><td>1.70</td><td>.55</td></tr><tr><td>5</td><td>4.83</td><td>1.70</td><td>.70</td><td>5.11</td><td>1.57</td><td>.66</td><td>5.13</td><td>1.53</td><td>.66</td></tr><tr><td>6</td><td>3.41</td><td>1.80</td><td>.63</td><td>3.73</td><td>1.78</td><td>.67</td><td>3.67</td><td>1.76</td><td>.62</td></tr><tr><td>7</td><td>4.72</td><td>1.77</td><td>.56</td><td>5.03</td><td>1.77</td><td>.45</td><td>4.98</td><td>1.84</td><td>.54</td></tr><tr><td>8</td><td>3.92</td><td>1.94</td><td>.68</td><td>4.13</td><td>1.76</td><td>.59</td><td>3.81</td><td>1.82</td><td>.52</td></tr><tr><td>9</td><td>4.07</td><td>1.89</td><td>.60</td><td>4.29</td><td>1.80</td><td>.67</td><td>4.11</td><td>1.69</td><td>.64</td></tr></tbody></table> </ephtml> </p> <p>A principal component analysis extracted one component with an eigenvalue of 4.82. This component accounted for 53.54% of the variance and its correlations with the nine individual items ranged from.64 to.78. The eigenvalues of the remaining components were all below 1.0, (i.e., 0.82, 0.72, 0.61, 0.53, 0.48., 0.38, 0.34, and 0.30), indicating no additional sources of common variance.</p> <hd id="AN0161473728-19">Correlations with other psychometric tests</hd> <p>Table 4 shows the correlations between the SSCS and other included measures in Study 1. A moderately strong correlation (<emph>r</emph> = .52) between the SSCS and the addiction scale (SAS‐SV) suggests considerable shared variance between the two tests. One item of the SAS‐SV deals with smartphone checking ("Constantly checking my smartphone so as not to miss conversations between other people on Twitter or Facebook"). However, the correlation between this item and the SSCS was in the range of the other SAS‐SV items and removing it from the SAS‐SV sum score did not notably lower the correlation with the SSCS (<emph>r</emph> = .51).</p> <p>4 TABLE Correlations between spontaneous smartphone checking and other included measures in Study 1 (N  = 209)</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Measure</th><th align="left">1</th><th align="left">2</th><th align="left">3</th><th align="left">4</th><th align="left">5</th><th align="left">6</th><th align="left">7</th><th align="left">8</th><th align="left">9</th></tr></thead><tbody valign="top"><tr><td>1. SSCS</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>2. SAS‐SV</td><td>.52<xref ref-type="fn" rid="tfn6" /></td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3. CES D</td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td>.44<xref ref-type="fn" rid="tfn6" /></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>4. MW‐D</td><td>.17<xref ref-type="fn" rid="tfn8" /></td><td>.14<xref ref-type="fn" rid="tfn8" /></td><td>.13</td><td /><td /><td /><td /><td /><td /></tr><tr><td>5. MW‐S</td><td>.27<xref ref-type="fn" rid="tfn6" /></td><td>.30<xref ref-type="fn" rid="tfn6" /></td><td>.44<xref ref-type="fn" rid="tfn6" /></td><td>.63<xref ref-type="fn" rid="tfn6" /></td><td /><td /><td /><td /><td /></tr><tr><td>6. IAMI<sup>1</sup></td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td>.30<xref ref-type="fn" rid="tfn6" /></td><td>.48<xref ref-type="fn" rid="tfn6" /></td><td>.42<xref ref-type="fn" rid="tfn6" /></td><td>.59<xref ref-type="fn" rid="tfn6" /></td><td /><td /><td /><td /></tr><tr><td>7. SCS‐R PRI</td><td>.14<xref ref-type="fn" rid="tfn8" /></td><td>.13</td><td>.10</td><td>.31<xref ref-type="fn" rid="tfn6" /></td><td>.29<xref ref-type="fn" rid="tfn6" /></td><td>.34<xref ref-type="fn" rid="tfn6" /></td><td /><td /><td /></tr><tr><td>8. SCS‐R PUB</td><td>.29<xref ref-type="fn" rid="tfn6" /></td><td>.33<xref ref-type="fn" rid="tfn6" /></td><td>.17<xref ref-type="fn" rid="tfn8" /></td><td>.11</td><td>.23<xref ref-type="fn" rid="tfn7" /></td><td>.33<xref ref-type="fn" rid="tfn6" /></td><td>.59<xref ref-type="fn" rid="tfn6" /></td><td /><td /></tr><tr><td>9. SCS‐R SOC</td><td>.05</td><td>.14<xref ref-type="fn" rid="tfn8" /></td><td>.31<xref ref-type="fn" rid="tfn6" /></td><td>.18<xref ref-type="fn" rid="tfn8" /></td><td>.34<xref ref-type="fn" rid="tfn6" /></td><td>.21<xref ref-type="fn" rid="tfn7" /></td><td>.21<xref ref-type="fn" rid="tfn7" /></td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td /></tr><tr><td>10. BSSS</td><td>.30<xref ref-type="fn" rid="tfn6" /></td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td>.29<xref ref-type="fn" rid="tfn6" /></td><td>.22<xref ref-type="fn" rid="tfn7" /></td><td>.31<xref ref-type="fn" rid="tfn6" /></td><td>.01</td><td>−.03</td><td>−.20<xref ref-type="fn" rid="tfn7" /></td></tr></tbody></table> </ephtml> </p> <ulist> <item>4 <sups>1</sups><emph>N</emph> = 202.</item> <item>5 Abbreviations: BSSS, brief sensations seeking scale; CES‐D, center for epidemiologic studies depression scale; IAMI, involuntary autobiographical memory inventory; MW‐D, mind‐wandering deliberate scale; MW‐S, mind‐wandering spontaneous scale; SAS‐SV, smartphone addiction scale—Short version; SCS‐R, self‐consciousness scale—Revised version: Private, Public and Social Anxiety subscales; SSCS, spontaneous smartphone checking.</item> <item>6 *** <emph>p</emph> < .001;</item> <item>7 ** <emph>p</emph> < .01;</item> <item>8 * <emph>p</emph> < .05.</item> </ulist> <p>An inspection of the correlation matrix in Table 4 also shows that the SSCS and SAS‐SV correlated similarly with most of the other included measures. Both the SSCS and the SAS‐SV correlated positively with measures of spontaneous thought, sensation seeking and public self‐consciousness. However, the two scales appeared to differ in the strength of their association with depression (CES‐D). The SAS‐SV showed a moderately strong correlation with the depression measure (<emph>r</emph> = .44) whereas a weaker relationship was observed for the SSCS (<emph>r</emph> = .22, see Table 4 for details). A comparison of the two correlations (following Diedenhofen & Musch, [<reflink idref="bib12" id="ref49">12</reflink>]) showed a significant difference (Steiger's <emph>z</emph> = 3.49, <emph>p</emph> = .005).</p> <p>As shown in Table 4, we also found moderately strong correlations between the measure of depressive symptoms (CES‐D) and the two included measures of unintended spontaneous thoughts: unintentional mind‐wandering (MW‐S) and involuntary autobiographical memory (IAMI). It therefore seemed plausible that the positive correlation between spontaneous smartphone checking and depressive symptoms might be driven by their shared association with unintentional, spontaneous thought. In order to further explore the differences between spontaneous smartphone checking and smartphone addiction, we examined if the association between depressive symptoms and spontaneous smartphone checking, as well as between depressive symptoms and smartphone addiction, would remain after controlling for the association with the two spontaneous thought measures. To do so, we conducted a regression analysis with depressive symptoms as measured by the CES‐D as the dependent variable and the SSCS, SAS‐SV, IAMI, and MW‐S as predictor variables. The regression equation in standardized beta weights, including all variables that were significant at the.05 level was CES‐D = .366 SAS‐SV + .295 IAMI + .164 MW‐S, <emph>R</emph><sups>2</sups> = .35, <emph>N</emph> = 202. When controlling for these other measures, the SSCS showed a non‐significant and negative relation (<emph>β</emph> = −.118, <emph>p</emph> > .08). Running the same analysis while including only the SSCS, the IAMI and the MW‐S as predictors (thus leaving out the SAS‐SV) rendered similar results in that the SSCS remained non‐significant (<emph>β</emph> = .055, <emph>p</emph> > .30). Thus, spontaneous smartphone checking showed no significant positive association with depressive symptoms once controlling for shared variance with measures of spontaneous thought, whereas the measure for smartphone addiction remained a substantial predictor (<emph>β</emph> = .366) of depressive symptoms, even when controlling for measures of spontaneous thoughts and spontaneous smartphone checking.</p> <hd id="AN0161473728-20">Summary and discussion</hd> <p>The internal consistency of the nine‐item SSCS was high. A principal component analysis revealed just one component, consistent with the SSCS capturing one psychological dimension. The predicted association with measures of spontaneous thought was also confirmed, in that the SSCS showed modest positive correlations with measures of spontaneous mind‐wandering and involuntary autobiographical memory frequency. Supporting its construct validity, the SSCS showed a moderately strong correlation with the included measure of smartphone addiction. The SSCS and the addiction scale showed a similar pattern of correlations with other included measures, except for depressive symptoms, for which the SSCS showed a weaker and less robust association that was rendered non‐significant when controlling for shared variance with spontaneous thought. In addition, both the SSCS and the SAS correlated positively with public self‐consciousness. This suggests that spontaneous checking and/or compulsive use of smartphones may be related to a concern for one's public appearance.</p> <hd id="AN0161473728-21">STUDY 2</hd> <p>Study 2 was conducted to replicate Study 1 using the final nine‐item version of the SSCS. In addition, we extended the test battery with two additional measures to further explore differences between spontaneous smartphone checking as measured by the SSCS and smartphone addiction as measured by the SAS‐SV.</p> <hd id="AN0161473728-22">Method</hd> <p></p> <hd id="AN0161473728-23">Participants</hd> <p>We recruited 256 participants from Amazon Mechanical Turk using CloudResearch (Litman et al., [<reflink idref="bib31" id="ref50">31</reflink>]); 114 women, 141 men and 1 person who indicated gender as "other." Mean age was 37.34 years (SD = 10.92), range 20–69. To be included in the study, the participants had to give informed consent, be native English speakers, own a smartphone, pass three attention checks, and provide meaningful answers to an open‐ended question. Each worker was paid 1.50 USD.</p> <hd id="AN0161473728-24">Material</hd> <p>Table 2 shows the descriptive statistics and reliability measures for the psychometric tests included in Study 2. In addition to the final version of the SSCS, we included the same measures as in Study 1, and two additional measures. Both added measures probed motivations for smartphone usage in daily life.</p> <hd id="AN0161473728-25">Spontaneous smartphone checking scale</hd> <p>The SSCS consists of nine items probing the tendency to spontaneously check one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goal in mind. Each item describes an everyday situation, for which the participant indicates his or her tendency to engage in spontaneous smartphone checking on a 7‐point scale (1 = never and 7 = extremely often). Sum scores range from 9 to 63.</p> <hd id="AN0161473728-26">Motivation for smartphone use</hd> <p>The motivation for smartphone use (MSU) scale is based on eight items divided into two subscales capturing entertainment and escapism motivations in smartphone use. The entertainment motivation subscale is covered by five items (e.g., "I use my smartphone because it's enjoyable"). Escapism motivation is measured through the remaining three items (e.g., "I use my smartphone so I can forget about school, work, or other things"). All questions are rated on a 5‐point Likert scale (Wang, Wang, et al., [<reflink idref="bib52" id="ref51">52</reflink>]). The scale items are adopted and recontextualized from of the original 'Social Media Usage Motivation Scale' (Wang, Jackson, et al., [<reflink idref="bib51" id="ref52">51</reflink>]).</p> <hd id="AN0161473728-27">Smartphone reliance for everyday tasks</hd> <p>We generated seven questions for the purpose of the present study to measure perceived reliance to one's smartphone during everyday life tasks. Reliance was deemed present, if the person faces difficulty, negative consequences, or is not able to uphold essential daily tasks by not having the smartphone accessible. The questions incorporate personal (e.g., "Organizing your daily life") social (e.g., "Being connected with friends and family") and societal (e.g., "Communication with public/private institutions") factors as possible active agents driving the reliance. All questions were rated on a 5‐point scale ranging from 0 = <emph>Not reliant</emph> (not having a smartphone would make no difference) to 5 = <emph>Completely reliant</emph> (I could not perform this activity without a smartphone). See Supporting Information for the full set of questions.</p> <hd id="AN0161473728-28">Procedure</hd> <p>As in Study 1, a task was created and advertised in Amazon Mechanical Turk using CloudResearch, and the data collection was conducted using the survey platform Qualtrics. Participants first answered an informed consent form and provided demographic information. They then answered the included scales in the following order: SSCS, BSSS, SCS, MW‐D and MW‐S, CES‐D, IAMI, SAS, smartphone reliance for everyday tasks (SPR), and MSU. They also answered three attention checks to ensure their continuous attentiveness throughout the survey. Upon completing the survey, participants received a code to be provided in Amazon Mechanical Turk to receive payment.</p> <hd id="AN0161473728-29">Results</hd> <p>In Study 2, we first examine the scale and item properties and whether they replicate those in Study 1. We next describe how the scale is associated with other measures. As in Study 1, we are especially interested in its relation to measures of smartphone addiction, spontaneous thought, and depression.</p> <hd id="AN0161473728-30">Scale and item properties</hd> <p>Table 3 shows the statistics for each individual item of the SSCS. As can be seen, the item‐total correlations are high for all items, consistent with Study 1, and means of individual items are comparable to those in Study 1. All are above the mid‐point of the 7‐point rating scale, suggesting that participants are familiar with engaging in spontaneous smartphone checking.</p> <p>Replicating Study 1, a principal component analysis suggested extracting one component based on an eigenvalue of 4.69, accounting for 52.10% of the variance. Its correlations with the nine individual items ranged from.54 to.82. The eigenvalue of all the remaining components were all below 1, (i.e., 0.88, 0.81, 0.71, 0.56, 0.38., 0.35, 0.34, and 0.29), offering no additional explanation for variance shared by the items.</p> <hd id="AN0161473728-31">Associations with other psychometric tests</hd> <p>Table 5 shows the correlations between the SSCS and the other included measures in Study 2. Overall, the pattern of correlations replicated Study 1. The SSCS correlated strongly with smartphone addiction and moderately with measures of depressive symptoms, spontaneous thought, private and public self‐consciousness and using the smartphone for entertainment and escapism. As in Study 1, the SSCS and the SAS‐SV showed a similar pattern of correlations, but the strength of the correlations varied for some variables. Again, the addiction scale (SAS‐SV) was more strongly associated with depressive symptoms (CES‐D) than the spontaneous smartphone checking measured by the SSCS (<emph>r</emph>s = .44 and.21, respectively; Steiger's <emph>z</emph> = 4.521, <emph>p</emph> < .001; Diedenhofen & Musch, [<reflink idref="bib12" id="ref53">12</reflink>]). The scales probing MSU (Escapism and Entertainment) and reliance on smartphone for everyday chores (SPR) correlated similarly with the SSCS and the SAS‐SV, and thus did not differentiate spontaneous smartphone checking from smartphone addiction.</p> <p>5 TABLE Correlations between spontaneous smartphone checking and other included measures in Study 2 (N  = 256)</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Measures</th><th align="left">1</th><th align="left">2</th><th align="left">3</th><th align="left">4</th><th align="left">5</th><th align="left">6</th><th align="left">7</th><th align="left">8</th><th align="left">9</th><th align="left">10</th><th align="left">11</th><th align="left">12</th></tr></thead><tbody valign="top"><tr><td>1. SSCS</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>2. SAS‐SV</td><td>.62<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3. CES D</td><td>.21<xref ref-type="fn" rid="tfn10" /></td><td>.44<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>4. MW‐D</td><td>.06</td><td>.21<xref ref-type="fn" rid="tfn10" /></td><td>.22<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>5. MW‐S</td><td>.22<xref ref-type="fn" rid="tfn10" /></td><td>.40<xref ref-type="fn" rid="tfn10" /></td><td>.40<xref ref-type="fn" rid="tfn10" /></td><td>.56<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>6. IAMI</td><td>.28<xref ref-type="fn" rid="tfn10" /></td><td>.40<xref ref-type="fn" rid="tfn10" /></td><td>.41<xref ref-type="fn" rid="tfn10" /></td><td>.41<xref ref-type="fn" rid="tfn10" /></td><td>.56<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>7. SCS‐R PRI</td><td>.22<xref ref-type="fn" rid="tfn10" /></td><td>.17<xref ref-type="fn" rid="tfn11" /></td><td>.21<xref ref-type="fn" rid="tfn10" /></td><td>.22<xref ref-type="fn" rid="tfn10" /></td><td>.26<xref ref-type="fn" rid="tfn10" /></td><td>.35<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /><td /></tr><tr><td>8. SCS‐R PUB</td><td>.27<xref ref-type="fn" rid="tfn10" /></td><td>.19<xref ref-type="fn" rid="tfn11" /></td><td>.24<xref ref-type="fn" rid="tfn10" /></td><td>.11</td><td>.24<xref ref-type="fn" rid="tfn11" /></td><td>.27<xref ref-type="fn" rid="tfn10" /></td><td>.60<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /><td /></tr><tr><td>9. SCS‐R SOC</td><td>.08</td><td>.19<xref ref-type="fn" rid="tfn11" /></td><td>.30<xref ref-type="fn" rid="tfn10" /></td><td>.10</td><td>.31<xref ref-type="fn" rid="tfn10" /></td><td>.21<xref ref-type="fn" rid="tfn10" /></td><td>.24<xref ref-type="fn" rid="tfn10" /></td><td>.40<xref ref-type="fn" rid="tfn10" /></td><td /><td /><td /><td /></tr><tr><td>10. BSSS</td><td>.15<xref ref-type="fn" rid="tfn12" /></td><td>.25<xref ref-type="fn" rid="tfn11" /></td><td>.23<xref ref-type="fn" rid="tfn10" /></td><td>.30<xref ref-type="fn" rid="tfn10" /></td><td>.41<xref ref-type="fn" rid="tfn10" /></td><td>.28<xref ref-type="fn" rid="tfn10" /></td><td>−.05</td><td>−.09</td><td>−.15<xref ref-type="fn" rid="tfn12" /></td><td /><td /><td /></tr><tr><td>11. MSU‐ESC</td><td>.44<xref ref-type="fn" rid="tfn10" /></td><td>.47<xref ref-type="fn" rid="tfn10" /></td><td>.32<xref ref-type="fn" rid="tfn10" /></td><td>.19<xref ref-type="fn" rid="tfn11" /></td><td>.31<xref ref-type="fn" rid="tfn10" /></td><td>.31<xref ref-type="fn" rid="tfn10" /></td><td>.18<xref ref-type="fn" rid="tfn11" /></td><td>.20<xref ref-type="fn" rid="tfn11" /></td><td>.19<xref ref-type="fn" rid="tfn11" /></td><td>.17<xref ref-type="fn" rid="tfn11" /></td><td /><td /></tr><tr><td>12. MSU‐ENT</td><td>.42<xref ref-type="fn" rid="tfn10" /></td><td>.35<xref ref-type="fn" rid="tfn10" /></td><td>.03</td><td>.17<xref ref-type="fn" rid="tfn11" /></td><td>.17<xref ref-type="fn" rid="tfn11" /></td><td>.18<xref ref-type="fn" rid="tfn11" /></td><td>.23<xref ref-type="fn" rid="tfn11" /></td><td>.26<xref ref-type="fn" rid="tfn10" /></td><td>.10</td><td>.02</td><td>.48<xref ref-type="fn" rid="tfn10" /></td><td /></tr><tr><td>13. SPR</td><td>.54<xref ref-type="fn" rid="tfn10" /></td><td>.53<xref ref-type="fn" rid="tfn10" /></td><td>.23<xref ref-type="fn" rid="tfn10" /></td><td>.03</td><td>.10</td><td>.18<xref ref-type="fn" rid="tfn11" /></td><td>.14<xref ref-type="fn" rid="tfn12" /></td><td>.20<xref ref-type="fn" rid="tfn11" /></td><td>.13<xref ref-type="fn" rid="tfn12" /></td><td>.05</td><td>.35<xref ref-type="fn" rid="tfn10" /></td><td>.27<xref ref-type="fn" rid="tfn10" /></td></tr></tbody></table> </ephtml> </p> <ulist> <item>9 Abbreviations: BSSS, brief sensations seeking scale; CES‐D, center for epidemiologic studies depression scale; IAMI, involuntary autobiographical memory inventory; MSU, motivation for smartphone use: Escapism and entertainment subscales; MW‐D, mind‐wandering deliberate scale; MW‐S, mind‐wandering spontaneous scale; SAS‐SV, smartphone addiction scale—Short version; SCS‐R, self‐consciousness scale—Revised version: Private, public and social anxiety subscales; SPR, smartphone reliance test, developed for the purpose of the present study; SSCS, spontaneous smartphone checking.</item> <item>10 *** <emph>p</emph> < .001;</item> <item>11 ** <emph>p</emph> < .01;</item> <item>12 * <emph>p</emph> < .05.</item> </ulist> <p>As in Study 1, depressive symptoms (CES‐D) correlated with both the SSCS and measures of unintended, spontaneous thought, suggesting that the positive correlation between spontaneous smartphone checking and depressive symptoms might be driven by their shared association with unintended thoughts. The same might apply to the measure of smartphone addiction (SAS‐SV). To disentangle these possibilities, and thereby to further examine differences between spontaneous smartphone checking and smartphone addiction, we ran the same analyses as we did in Study 1 to examine if the association between depressive symptoms and these two measures would remain significant after controlling for the association with the two measures of unintentional spontaneous thought. We conducted a regression analysis with depressive symptoms as measured by the CES‐D as the dependent variable and the SSCS, SAS‐SV, IAMI, and MW‐S as predictor variables. The regression equation in standardized beta weights, including all variables that were significant at the.05 level was CES‐D = .347 SAS‐SV + . 210 IAMI + .168 MW‐S, <emph>R</emph><sups><emph>2</emph></sups> = .28, <emph>N</emph> = 256. The SSCS was not a significant predictor in the analysis (<emph>β</emph> = −.098, <emph>p</emph> > .1). Running the same analysis while including only the SSCS, the IAMI and the MW‐S as predictors (thus leaving out the SAS‐SV) rendered similar results in that the SSCS remained non‐significant in the regression analysis (<emph>β</emph> = .089, <emph>p</emph> > .10). Thus, as in Study 1, spontaneous smartphone checking showed no significant association with depressive symptoms after controlling for shared variance with measures of spontaneous thought, whereas the smartphone addiction measure (SAS‐SV) again remained the numerically largest predictor of depressive symptoms, even when controlling for spontaneous thought measures as well as for the SSCS.</p> <hd id="AN0161473728-32">Summary and discussion</hd> <p>The nine‐item SSCS showed good psychometric properties and meaningful correlations with other variables, largely replicating Study 1. The SSCS correlated positively with measures of spontaneous thought and with using the phone for escapism purposes, consistent with the assumption of spontaneous smartphone checking being viewed as a kind of "digital daydreaming." As in Study 1, the SSCS also showed a strong positive correlation with smartphone addiction, and the two scales showed similar patterns of correlations with other included measures, but the addiction scale showed a stronger and more robust association with depressive symptoms. As in Study 1, the SSCS and the SAS‐SV correlated positively with public self‐consciousness, suggesting an association between spontaneous smartphone checking as well as smartphone addiction and conscious awareness of one's public appearance.</p> <hd id="AN0161473728-33">STUDY 3</hd> <p>Studies 1 and 2 established that the SSCS had good psychometric properties. Although correlated, it differed from a measure of smartphone addiction by showing weaker associations with depression, which (unlike for smartphone addiction) disappeared when controlling for shared variance with measures of spontaneous thought. This supports an interpretation of scores on the SSCS as reflecting a common and non‐pathological dimension of smartphone usage.</p> <p>As pointed out in the introduction, there are a number of reasons to assume spontaneous smartphone checking to be especially likely to occur during situations and activities that otherwise would foster internally directed daydreaming, such as during waiting time and less attention demanding activities. If for any given individual, the two activities would need to be carried out during the same off‐task moments in everyday life, engaging in smartphone checking rather than in daydreaming (and vice versa) might have broader implications for mental life, especially if smartphone checking and daydreaming are differentially associated with other types of mental and media behaviors. To explore this question, we examined the relation between spontaneous smartphone checking, other measures of digital media usage, a well‐established measure of daydreaming frequency, as well as additional measures of internally generated thought and self‐consciousness. We expected that the tendency to spontaneously checking one's phone would be less strongly associated with measures of self‐consciousness and internal thought, including reflection and rumination, than would the tendency to engage in daydreaming and mind‐wandering. We also expected people who are prone to spontaneously checking their phone to be more focused on their appearance on social media and generally more reliant on using their phone in everyday life, than people more prone to engage in daydreaming and mind‐wandering directed toward internal thoughts.</p> <hd id="AN0161473728-34">Method</hd> <p></p> <hd id="AN0161473728-35">Participants</hd> <p>We recruited 202 participants from Amazon Mechanical Turk using CloudResearch (Litman et al., [<reflink idref="bib31" id="ref54">31</reflink>]); 102 women, 98 men, and two people who indicated gender as "other." Mean age was 38.36 years (SD = 10.37), range 22–69. The inclusion criteria were the same as in Studies 1 and 2. Each worker was paid 2 USD.</p> <hd id="AN0161473728-36">Material</hd> <p>Table 2 shows the descriptive statistics and reliability measures for the psychometric tests included in Study 3. In addition to our measure of SSCS, the scales for smartphone addiction (SAS‐SV) and smartphone reliance (SPR), we included the measures used in Studies 1 and 2 that probed mind‐wandering (MW‐D, MW‐S) and self‐consciousness (SCS‐R). We additionally included measures of daydreaming frequency, rumination and reflection, public and private self‐absorption, and appearance related social media consciousness (ASMC).</p> <hd id="AN0161473728-37">Daydreaming frequency scale</hd> <p>This scale is a widely used measure of the tendency to engage in daydreaming in everyday life. It is adapted from Singer and Antrobus ([<reflink idref="bib44" id="ref55">44</reflink>]) by Giambra ([<reflink idref="bib18" id="ref56">18</reflink>]). The scale consists of 12 items addressing the tendency to engage in daydreaming in everyday life, such as "I lose myself in active daydreaming." Each item is answered on a 5‐point scale (0–4) indicating frequency. The sum score can range from 0 to 48.</p> <hd id="AN0161473728-38">Rumination‐reflection questionnaire</hd> <p>This questionnaire consists of two subscales, rumination and reflection, both measuring heightened attention to the self, and both consisting of 12 items rated on a 5‐point scale (with 1 = <emph>strongly disagree</emph> and 5 = <emph>strongly agree</emph>). The rumination subscale addresses "self‐attentiveness motivated by perceived threats, losses, or injustices to the self," whereas the reflection subscale addresses "self‐attentiveness motivated by curiosity or epistemic interest in the self" (Trapnell & Campbell, [<reflink idref="bib50" id="ref57">50</reflink>], p. 297). Rumination includes items such as "My attention is often focused on aspects of myself I wish I'd stop thinking about," whereas reflection includes items such as "I love exploring my 'inner' self." Sum scores range from 12 to 60 (Trapnell & Campbell, [<reflink idref="bib50" id="ref58">50</reflink>]).</p> <hd id="AN0161473728-39">Self‐absorption scale</hd> <p>This measure probes an excessive, sustained, and rigid focus on oneself. It consists of two subscales: private self‐absorption (eight items, e.g., "I think about myself more than anything else") and public self‐absorption (nine items, e.g., "It upsets me when people I meet don't like me"). Response options for the 17 items range from <emph>Not at all like me</emph> (<reflink idref="bib1" id="ref59">1</reflink>) to <emph>Very much like m</emph>e (<reflink idref="bib5" id="ref60">5</reflink>). A sum score was generated for each of the two subscales (McKenzie & Hoyle, [<reflink idref="bib33" id="ref61">33</reflink>]).</p> <hd id="AN0161473728-40">Appearance‐related social media consciousness scale</hd> <p>This scale seeks to capture the degree of awareness on one's appearance and attractiveness on social media. The scale is developed toward adolescents and contains 13 items (e.g., "My attractiveness in pictures is more important than anything else I do on social media"); range is from 1 = <emph>Never</emph> to 7 = <emph>Always</emph>. A mean score was generated (Choukas‐Bradley et al., [<reflink idref="bib11" id="ref62">11</reflink>]).</p> <hd id="AN0161473728-41">Procedure</hd> <p>As in Studies 1 and 2, a task was created and advertised in Amazon Mechanical Turk using CloudResearch, and the data collection was conducted using the survey platform Qualtrics. Participants first gave informed consent and provided demographic information. They then answered the included scales in the following order: SSCS, rumination‐reflection questionnaire (RRQ), MW‐D and MW‐S, SAS, daydreaming frequency scale (DDFS), SCS‐R, ASMC, SAS, and SPR. They also answered three attention checks to ensure their continuous attentiveness throughout the survey.</p> <hd id="AN0161473728-42">Results</hd> <p>Because the scale and item properties of the SSCS were established in Studies 1 and 2, we here focus on the relations between SSCS and the included measures of daydreaming and mind‐wandering as well as their differential associations with other scales.</p> <p>As shown in Table 6, the SSCS did not correlate significantly with the measure of DDFS and correlated only weakly with MW‐D, suggesting that people who frequently engage in spontaneous smartphone checking are not particularly prone to engage in daydreaming and deliberate mind‐wandering. There was a moderate correlation with MW‐S. These measures showed differential patterns of correlations with other included measures: DDFS and MW‐D correlated moderately to strongly with measures of self‐consciousness, rumination and reflection, but only weakly with smartphone addiction, appearance related social media consciousness and everyday smartphone reliance (Table 6). Spontaneous smartphone checking, on the other hand, tended to show a different pattern of associations, in terms of generally weaker correlations with self‐consciousness, rumination and reflection, and stronger correlations with measures of smartphone addiction, appearance related social media consciousness, and daily smartphone reliance.</p> <p>6 TABLE Correlations between spontaneous smartphone checking and other included measures in Study 3 (N  = 202)</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Measures</th><th align="left">1</th><th align="left">2</th><th align="left">3</th><th align="left">4</th><th align="left">5</th><th align="left">6</th><th align="left">7</th><th align="left">8</th><th align="left">9</th><th align="left">10</th><th align="left">11</th><th align="left">12</th><th align="left">13</th></tr></thead><tbody valign="top"><tr><td>1. SSCS</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>2. DDFS</td><td>.13</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3. MW‐D</td><td>.17<xref ref-type="fn" rid="tfn17" /></td><td>.48<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>4. MW‐S</td><td>.36<xref ref-type="fn" rid="tfn15" /></td><td>.54<xref ref-type="fn" rid="tfn15" /></td><td>.42<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>5. SCS‐R PRI</td><td>.31<xref ref-type="fn" rid="tfn15" /></td><td>.48<xref ref-type="fn" rid="tfn15" /></td><td>.41<xref ref-type="fn" rid="tfn15" /></td><td>.46<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>6. SCS‐R PUB</td><td>.26<xref ref-type="fn" rid="tfn15" /></td><td>.30<xref ref-type="fn" rid="tfn15" /></td><td>.23<xref ref-type="fn" rid="tfn16" /></td><td>.43<xref ref-type="fn" rid="tfn15" /></td><td>.60<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>7. SCS‐R SOC</td><td>.08</td><td>.40<xref ref-type="fn" rid="tfn15" /></td><td>.11</td><td>.44<xref ref-type="fn" rid="tfn15" /></td><td>.30<xref ref-type="fn" rid="tfn15" /></td><td>.51<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>8. RRQ‐RUM</td><td>.25<xref ref-type="fn" rid="tfn15" /></td><td>.47<xref ref-type="fn" rid="tfn15" /></td><td>.24<xref ref-type="fn" rid="tfn15" /></td><td>.62<xref ref-type="fn" rid="tfn15" /></td><td>.46<xref ref-type="fn" rid="tfn16" /></td><td>.60<xref ref-type="fn" rid="tfn15" /></td><td>.58<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /><td /><td /><td /></tr><tr><td>9. RRQ‐REF</td><td>.16<xref ref-type="fn" rid="tfn17" /></td><td>.25<xref ref-type="fn" rid="tfn15" /></td><td>.50<xref ref-type="fn" rid="tfn15" /></td><td>.23<xref ref-type="fn" rid="tfn15" /></td><td>.61<xref ref-type="fn" rid="tfn15" /></td><td>.24<xref ref-type="fn" rid="tfn15" /></td><td>.01</td><td>.15<xref ref-type="fn" rid="tfn17" /></td><td /><td /><td /><td /><td /></tr><tr><td>10. PrSA</td><td>.35<xref ref-type="fn" rid="tfn15" /></td><td>.37<xref ref-type="fn" rid="tfn16" /></td><td>.22<xref ref-type="fn" rid="tfn16" /></td><td>.55<xref ref-type="fn" rid="tfn15" /></td><td>.47<xref ref-type="fn" rid="tfn15" /></td><td>.38<xref ref-type="fn" rid="tfn15" /></td><td>.35<xref ref-type="fn" rid="tfn15" /></td><td>.44<xref ref-type="fn" rid="tfn15" /></td><td>.12</td><td /><td /><td /><td /></tr><tr><td>11. PubSA</td><td>.27<xref ref-type="fn" rid="tfn15" /></td><td>.40<xref ref-type="fn" rid="tfn15" /></td><td>.18<xref ref-type="fn" rid="tfn17" /></td><td>.57<xref ref-type="fn" rid="tfn15" /></td><td>.39<xref ref-type="fn" rid="tfn15" /></td><td>.63<xref ref-type="fn" rid="tfn15" /></td><td>.57<xref ref-type="fn" rid="tfn15" /></td><td>.63<xref ref-type="fn" rid="tfn15" /></td><td>.07</td><td>.70<xref ref-type="fn" rid="tfn15" /></td><td /><td /><td /></tr><tr><td>12. SAS‐SV</td><td>.52<xref ref-type="fn" rid="tfn15" /></td><td>.24<xref ref-type="fn" rid="tfn15" /></td><td>.15<xref ref-type="fn" rid="tfn17" /></td><td>.43<xref ref-type="fn" rid="tfn15" /></td><td>.27<xref ref-type="fn" rid="tfn15" /></td><td>.33<xref ref-type="fn" rid="tfn15" /></td><td>.21<xref ref-type="fn" rid="tfn16" /></td><td>.29<xref ref-type="fn" rid="tfn15" /></td><td>.02</td><td>.55<xref ref-type="fn" rid="tfn15" /></td><td>.50<xref ref-type="fn" rid="tfn15" /></td><td /><td /></tr><tr><td>13. SPR</td><td>.55<xref ref-type="fn" rid="tfn15" /></td><td>.11</td><td>.17<xref ref-type="fn" rid="tfn17" /></td><td>.29<xref ref-type="fn" rid="tfn15" /></td><td>.37<xref ref-type="fn" rid="tfn15" /></td><td>.32<xref ref-type="fn" rid="tfn15" /></td><td>.04</td><td>.19<xref ref-type="fn" rid="tfn16" /></td><td>.16<xref ref-type="fn" rid="tfn17" /></td><td>.38<xref ref-type="fn" rid="tfn15" /></td><td>.25<xref ref-type="fn" rid="tfn15" /></td><td>.56<xref ref-type="fn" rid="tfn15" /></td><td /></tr><tr><td>14. ASMC</td><td>.44<xref ref-type="fn" rid="tfn15" /></td><td>.19<xref ref-type="fn" rid="tfn16" /></td><td>.18<xref ref-type="fn" rid="tfn17" /></td><td>.33<xref ref-type="fn" rid="tfn15" /></td><td>.37<xref ref-type="fn" rid="tfn15" /></td><td>.49<xref ref-type="fn" rid="tfn15" /></td><td>.24<xref ref-type="fn" rid="tfn15" /></td><td>.32<xref ref-type="fn" rid="tfn15" /></td><td>.13</td><td>.58</td><td>.54<xref ref-type="fn" rid="tfn15" /></td><td>.59<xref ref-type="fn" rid="tfn15" /></td><td>.46<xref ref-type="fn" rid="tfn15" /></td></tr></tbody></table> </ephtml> </p> <ulist> <item>13 <emph>Note</emph>: <emph>N</emph> = 202.</item> <item>14 Abbreviations: ASMC, the appearance‐related social media consciousness scale; DDFS, daydreaming frequency scale; MW‐D, mind‐wandering deliberate scale; MW‐S, mind‐wandering spontaneous scale; PrSA, private self‐absorption; PubSA, public self‐absorption; RRQ‐RUM, the rumination and reflection questionnaire, reflection subscale; RRQ‐RUM, the rumination and reflection questionnaire, rumination subscale; SAS‐SV, smartphone addiction scale—Short version; SCS‐R, self‐consciousness scale—Revised version: Private, public and social anxiety subscales; SPR, smartphone reliance; SSCS, spontaneous smartphone checking.</item> <item>15 *** <emph>p</emph> < .001;</item> <item>16 ** <emph>p</emph> < .01;</item> <item>17 * <emph>p</emph> < .05.</item> </ulist> <p>To more systematically examine if spontaneous smartphone checking and daydreaming were differently associated with measures of other mental and digital behaviors, we conducted an exploratory factor analysis of scores on the full set of scales. Principal factors extraction identified three factors with eigenvalues of 5.77, 1.81, and 1.63 for Factors 1, 2, and 3, respectively (remaining eigenvalues <1.0). We obliquely rotated the three‐factor solution using the Oblimin method (interfactor <emph>r</emph>s provided in Table 7).</p> <p>7 TABLE Rotated factor pattern in Study 3, with loadings rank‐ordered for each factor</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Scales</th><th align="left">Factor 1</th><th align="left">Factor 2</th><th align="left">Factor 3</th></tr></thead><tbody valign="top"><tr><td>SCS‐R SOCIAL</td><td>.784</td><td>−.118</td><td>−.076</td></tr><tr><td>PubSA</td><td>.769</td><td>.269</td><td>−.135</td></tr><tr><td>RRQ‐RUM</td><td>.746</td><td>.009</td><td>.094</td></tr><tr><td>SCS‐R PUBLIC</td><td>.567</td><td>.177</td><td>.157</td></tr><tr><td>MW‐S</td><td>.540</td><td>.180</td><td>.239</td></tr><tr><td>DDFS</td><td>.486</td><td>−.088</td><td>.383</td></tr><tr><td>SAS‐SV</td><td>.132</td><td>.750</td><td>−.120</td></tr><tr><td>SPR</td><td>−.146</td><td>.739</td><td>.101</td></tr><tr><td>SSCS</td><td>−.080</td><td>.668</td><td>.091</td></tr><tr><td>ASMC</td><td>.191</td><td>.653</td><td>−.036</td></tr><tr><td>PrSA</td><td>.426</td><td>.500</td><td>−.013</td></tr><tr><td>RRQ‐REF</td><td>−.122</td><td>.003</td><td>.775</td></tr><tr><td>SCS‐R PRIVAT</td><td>.239</td><td>.182</td><td>.640</td></tr><tr><td>MW‐D</td><td>.075</td><td>.012</td><td>.624</td></tr><tr><td align="left">Interfactor correlation</td></tr><tr><td>Factor 2</td><td>.40</td><td /><td /></tr><tr><td>Factor 3</td><td>.31</td><td>.27</td><td /></tr></tbody></table> </ephtml> </p> <ulist> <item>18 <emph>Note</emph>: <emph>N</emph> = 202; Bold fonts indicate highest factor loadings.</item> <item>19 Abbreviations: ASMC, the appearance‐related social media consciousness scale; DDFS, daydreaming frequency scale; MW‐D, mind‐wandering deliberate scale; MW‐S, mind‐wandering spontaneous scale; PrSA, private self‐absorption; PubSA, public self‐absorption; RRQ‐RUM, the rumination and reflection questionnaire, reflection subscale; RRQ‐RUM, the rumination and reflection questionnaire, rumination subscale; SAS‐SV, smartphone addiction scale—Short version; SCS‐R, self‐consciousness scale—Revised version: Private, public and social anxiety subscales; SPR, smartphone reliance; SSCS, spontaneous smartphone checking.</item> </ulist> <p>Table 7 shows the rotated factor pattern with the loadings for the included variables. All measures related to digital communication (SAS‐SV, SPR, SSCS, and ASMC) loaded highly on Factor 2, and had low loadings on the other two factors. This separated them from the remaining measures, which loaded most highly on either Factor 1 or 3, with low loadings on Factor 2. The only exception from this pattern was private self‐absorption (PrSA), for which loadings on Factors 1 and 2 exceeded typical salience criteria.</p> <p>Spontaneous thought measures (DDFS, MW‐S, RRQ‐Rumination) that are less controlled and usually correlated with negative affect loaded most highly on Factor 1. Tendencies to be concerned about one's public appearance and other people's judgments (SCS‐R‐social, SCS‐R‐public, PubSA) likewise loaded most strongly on Factor 1. The three remaining measures (RRQ‐REF, MW‐D and SCS‐R‐private) loaded most highly on Factor 3. An overarching property shared by these three measures is no clear association with negative affect, which may have separated them from measures loading in Factor 1.</p> <hd id="AN0161473728-43">Summary and discussion</hd> <p>Spontaneous smartphone checking was most strongly associated with other measures of digital communication and behaviors. Measures of spontaneous thought and self‐consciousness loaded on two different factors, which appeared to separate in accordance with associations with negative affectivity (or lack thereof) and levels of control. One exception to this pattern was private self‐absorption, which loaded slightly higher on the factor with smartphone checking and other measures of digital behavior than the factor reflecting negative affectivity. This may reflect greater dependency of smartphones in people who tend to think excessively about themselves, possibly in order to check their appearance on social media. Taken together the findings are consistent with the assumption of spontaneous smartphone checking serving different mental and social functions in daily life compared to internally directed daydreaming and mind‐wandering. Whereas internally directed daydreaming and mind‐wandering are more strongly associated with self‐consciousness, reflection and rumination, spontaneous smartphone checking is more strongly associated with other aspects of digital communication and public appearance on social media.</p> <hd id="AN0161473728-44">GENERAL DISCUSSION</hd> <p>Most individual differences tests for smartphone usage have addressed problematic or compulsive ways of interacting with smartphones, often conceptualized as smartphone addiction (Harris et al., [<reflink idref="bib19" id="ref63">19</reflink>]). Little is known about individual differences in everyday, non‐pathological uses of one's smartphone.</p> <p>Here we have introduced a new psychometric test for everyday smartphone usage focusing on <emph>spontaneous smartphone checking</emph>—that is, a direction of attention toward one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goal in mind. Conceptually, we regard this behavior as a parallel to spontaneous thought processes such as daydreaming or mind‐wandering. We do so because spontaneous smartphone checking appears to take place in situations, such as during waiting time or relaxation that, under other conditions, typically would trigger daydreaming directed toward internal thought. Like daydreaming, spontaneous smartphone checking is conceived as task‐unrelated and expected to often degrade performance on a parallel task (e.g., driving).</p> <p>The SSCS showed good psychometric properties, and correlated meaningfully with other measures of digital communication, underscoring its construct validity. It differed from a measure of problematic smartphone usage (i.e., smartphone addiction) by showing only a weak positive association with depressive symptoms, which disappeared when controlling for shared variance with measures of spontaneous thought. This underscores the SSCS as measuring a non‐pathological, habitual dimension of everyday smartphone usage.</p> <p>We examined the relation between the SSCS and other measures of digital media usage as well as measures of daydreaming, mind‐wandering and self‐consciousness using exploratory factor analysis. The SSCS separated from measures of daydreaming and deliberate mind‐wandering by loading highly on a factor associated with measures of other aspects of digital communication and public appearance on social media, and by not loading on dimensions related to self‐consciousness, reflection and rumination. Taken together, this suggests that spontaneous smartphone checking serves different mental and social functions than internally directed spontaneous thought processes.</p> <p>Overall, the present findings are consistent with the assumption that spontaneous smartphone checking is common in everyday life and, by competing for the same off‐task moments, to some extent, may replace daydreaming and mind‐wandering directed toward internal thoughts. However, due to the correlational nature of the data, causal inferences cannot be drawn. Nonetheless, consistent with the replacement assumption, Ralph et al. ([<reflink idref="bib36" id="ref64">36</reflink>]) found that when participants were given the opportunity to attend to an external media distractor (e.g., a video) during a cognitive task, reports of being off‐task increased, but the tendency to mind wander during the off‐task episodes was significantly reduced relative to attending the external media. This can be seen as consistent with other lines of research showing that people experience being pulled into digital off‐task activities (e.g., checking social media) during educational activities that involve the use of digital devices, such as computers and tablets (Aagaard, [<reflink idref="bib1" id="ref65">1</reflink>], [<reflink idref="bib2" id="ref66">2</reflink>]).</p> <p>Thus, it appears likely that for individual smartphone users, the time spent on spontaneous smartphone checking reduces the time spent on internally directed daydreaming, given that the same time obviously cannot be used twice. Although one activity might prompt the other, this still would be an instance of switching between activities, not engaging in them simultaneously. Importantly, this trade‐off would unfold at the level of the individual and not necessarily as observable differences between people. In other words, we should not necessarily expect negative correlations between the tendency to engage in spontaneous smartphone checking and internally directed daydreaming, respectively, when analyzed as differences between people. This is because people vary on many other dimensions, such as their general tendency to engage in off‐task activities. However, for a given individual with a limited amount of off‐task moments available in daily life, increasing the frequency of spontaneous smartphone checking during such moments would be negatively associated with internally generated daydreaming during the same moments.</p> <p>To the extent that spontaneous smartphone checking actually takes up time that an individual under other circumstances could have spent on internally oriented daydreaming, this could have detrimental long‐term effects on people's everyday functioning, following theories that daydreaming and mind‐wandering serve adaptive functions in daily life. According to the goal theory of current concerns (e.g., Klinger, [<reflink idref="bib22" id="ref67">22</reflink>], [<reflink idref="bib23" id="ref68">23</reflink>]; Klinger et al., [<reflink idref="bib24" id="ref69">24</reflink>], for review), the content of spontaneous thought reflects an individual's current concerns, defined as "the state of an organism between the time it becomes committed to pursuing a goal and the time it either gains the goal or abandons the pursuit" (Klinger, [<reflink idref="bib22" id="ref70">22</reflink>], p. 249). According to this theory, daydreaming and similar types of spontaneous thoughts will often happen in response to concern‐relevant cues and thereby remind the individual of the goal pursuit also during times when goal‐directed behavior is not feasible. Consistent with mind‐wandering supporting long‐term goal‐pursuit, a number of studies have shown that mind‐wandering typically is future oriented (e.g., Baird et al., [<reflink idref="bib4" id="ref71">4</reflink>]) and associated with reduced delay discounting (Klinger et al., [<reflink idref="bib24" id="ref72">24</reflink>]; Smallwood et al., [<reflink idref="bib46" id="ref73">46</reflink>] for review). There is also some evidence that a period of mind‐wandering helps the formation of creative solutions to problem solving (Baird et al., [<reflink idref="bib3" id="ref74">3</reflink>]).</p> <p>Past directed spontaneous thoughts, such as involuntary autobiographical memories (Berntsen, [<reflink idref="bib6" id="ref75">6</reflink>]), serve functions related to identity, problem solving, and social relationships (Rasmussen et al., [<reflink idref="bib37" id="ref76">37</reflink>]). More broadly, they may provide an opportunity for re‐evaluating past events and adjusting future goals and behaviors in the light of the present situation (Berntsen, [<reflink idref="bib7" id="ref77">7</reflink>]), thus stimulating reflection.</p> <p>Spontaneously checking one's smartphone is unlikely to involve similar functional benefits as the ones attributed to daydreaming and related types of spontaneous thoughts, because smartphone checking is less likely to give access to the same information as internally generated thoughts. Thus, if daydreaming on a regular basis supports long‐term goal‐pursuit and planning (Klinger et al., [<reflink idref="bib24" id="ref78">24</reflink>]), replacing it by spontaneous smartphone checking may lead to more prospective memory errors, less adaptive decisions, and less reflection. On the other hand, spontaneous smartphone checking could have other adaptive benefits, for example by diverting people from ruminative thoughts and keeping them updated on news events in the world or in relevant social circuits. Possible adaptive functions of spontaneous smartphone checking remain to be clarified along with potential negative long‐term effects.</p> <hd id="AN0161473728-45">Limitations and future directions</hd> <p>The present series of studies suffer from the same limitations as much of the current literature on smartphone usage. First, the SSCS is based on self‐reports, which are known to be only modestly correlated with actual behavior (Ellis et al., [<reflink idref="bib14" id="ref79">14</reflink>]; Wilmer et al., [<reflink idref="bib54" id="ref80">54</reflink>]), and the correlational design of the studies does not permit causal inferences. The ubiquity of smartphone usage complicates experimental manipulation with random assignment to different technology exposure (Wilmer et al., [<reflink idref="bib54" id="ref81">54</reflink>]). Still, future research should aim at developing research strategies for addressing causal connections and long‐term effects that do not rely solely on self‐reported smartphone use.</p> <p>Second, the SSCS focuses on spontaneous smartphone checking and does not address other aspects of inattentional smartphone usage. We were able to identify only one other psychometric test for habitual and absent‐minded smartphone usage: The smartphone use questionnaire‐absent‐minded (Marty‐Dugas et al., [<reflink idref="bib32" id="ref82">32</reflink>]). However, in contrast to the SSCS, this questionnaire correlated strongly (<emph>r</emph> > .70) with a measure of general smartphone usage and its associations with negative affect is unclear. Future research should address spontaneous smartphone checking in relation to this and broader measures of everyday inattention. Specifically, it would be relevant to examine how spontaneous smartphone checking relates to individual differences in executive functioning and attentional control.</p> <p>Third, there is evidence that mind‐wandering accounts for about 30%–50% of our conscious waking thoughts (Klinger et al., [<reflink idref="bib24" id="ref83">24</reflink>]). There is also evidence that people spend substantial amounts of time using their phone, although assessments vary across studies (Liebherr et al., [<reflink idref="bib30" id="ref84">30</reflink>]). However, it remains to be clarified how many times per day people spontaneously check their smartphone, the duration of each check, and how these behaviors vary with the context, individual dispositions, and ongoing tasks.</p> <hd id="AN0161473728-46">Conclusion</hd> <p>The SSCS measures the tendency to direct attention toward one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goals in mind. The scale showed good psychometric properties and correlated meaningfully with other psychometric tests. For individual phone users, spontaneous smartphone checking to some extent may replace daydreaming and mind‐wandering directed toward internal thoughts during undemanding everyday moments. Future research should clarify the extent and long‐term consequences of such replacement.</p> <hd id="AN0161473728-47">AUTHOR CONTRIBUTIONS</hd> <p>Dorthe Berntsen, Rick H. Hoyle, Daniel Munkholm Møller, and David C. Rubin conceived and designed the study. Daniel Munkholm Møller was responsible for collecting the data for the individual studies, with input from Dorthe Berntsen, who analyzed the data. Rick H. Hoyle was responsible for conducting and reporting the factor analysis in Study 3. Dorthe Berntsen wrote the first draft for the manuscript, with contributions from Daniel Munkholm Møller, Rick H. Hoyle, and David C. Rubin. All authors commented on the manuscript and approved the final version.</p> <hd id="AN0161473728-48">FUNDING INFORMATION</hd> <p>This research was supported by the Independent Research Fund, Denmark [9037‐00015B9], and the Danish National Research Foundation [DNRF89]. The funding sources had no role in the study design, data collection, analysis or interpretation of the data, writing of the manuscript, or the decision to submit the paper for publication.</p> <hd id="AN0161473728-49">CONFLICT OF INTEREST</hd> <p>We have no conflicts of interest to disclose.</p> <hd id="AN0161473728-50">DATA AVAILABILITY STATEMENT</hd> <p>The data that support the findings of this study are available from the corresponding author upon reasonable request and in accordance with the General Data Protection Regulation as administered by Aarhus University.</p> <p>GRAPH: DATA S1. Supporting Information</p> <ref id="AN0161473728-51"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref36" type="bt">1</bibl> <bibtext> For detailed information on number of excluded participants in Studies 1–3, see Supporting Information.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref48" type="bt">2</bibl> <bibtext> The four excluded items were"When I am bored," "At the dinner table," "When I am waiting for someone or something," and "When I am commuting."</bibtext> </blist> <blist> <bibl id="bib3" idref="ref74" type="bt">3</bibl> <bibtext> Funding information Danmarks Grundforskningsfond, Grant/Award Number: DNRF89; Det Frie Forskningsråd, Grant/Award Number: 9037‐00015B9</bibtext> </blist> </ref> <ref id="AN0161473728-52"> <title> REFERENCES </title> <blist> <bibtext> Aagaard, J. (2015). Drawn to distraction: A qualitative study of off‐task use of educational technology. Computers & Education, 87, 90 – 97.</bibtext> </blist> <blist> <bibtext> Aagaard, J. (2021). 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Rubin</p> <p>Reported by Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib34" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib26" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib38" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib17" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib13" firstref="ref5"></nolink> <nolink nlid="nl6" bibid="bib27" firstref="ref6"></nolink> <nolink nlid="nl7" bibid="bib53" firstref="ref7"></nolink> <nolink nlid="nl8" bibid="bib19" firstref="ref8"></nolink> <nolink nlid="nl9" bibid="bib25" firstref="ref9"></nolink> <nolink nlid="nl10" bibid="bib54" firstref="ref10"></nolink> <nolink nlid="nl11" bibid="bib15" firstref="ref12"></nolink> <nolink nlid="nl12" bibid="bib40" firstref="ref13"></nolink> <nolink nlid="nl13" bibid="bib43" firstref="ref14"></nolink> <nolink nlid="nl14" bibid="bib47" firstref="ref15"></nolink> <nolink nlid="nl15" bibid="bib21" firstref="ref16"></nolink> <nolink nlid="nl16" bibid="bib23" firstref="ref17"></nolink> <nolink nlid="nl17" bibid="bib24" firstref="ref18"></nolink> <nolink nlid="nl18" bibid="bib42" firstref="ref20"></nolink> <nolink nlid="nl19" bibid="bib41" firstref="ref24"></nolink> <nolink nlid="nl20" bibid="bib45" firstref="ref25"></nolink> <nolink nlid="nl21" bibid="bib16" firstref="ref28"></nolink> <nolink nlid="nl22" bibid="bib49" firstref="ref29"></nolink> <nolink nlid="nl23" bibid="bib36" firstref="ref30"></nolink> <nolink nlid="nl24" bibid="bib48" firstref="ref33"></nolink> <nolink nlid="nl25" bibid="bib31" firstref="ref35"></nolink> <nolink nlid="nl26" bibid="bib10" firstref="ref38"></nolink> <nolink nlid="nl27" bibid="bib28" firstref="ref40"></nolink> <nolink nlid="nl28" bibid="bib29" firstref="ref41"></nolink> <nolink nlid="nl29" bibid="bib35" firstref="ref42"></nolink> <nolink nlid="nl30" bibid="bib39" firstref="ref45"></nolink> <nolink nlid="nl31" bibid="bib20" firstref="ref46"></nolink> <nolink nlid="nl32" bibid="bib12" firstref="ref49"></nolink> <nolink nlid="nl33" bibid="bib52" firstref="ref51"></nolink> <nolink nlid="nl34" bibid="bib51" firstref="ref52"></nolink> <nolink nlid="nl35" bibid="bib44" firstref="ref55"></nolink> <nolink nlid="nl36" bibid="bib18" firstref="ref56"></nolink> <nolink nlid="nl37" bibid="bib50" firstref="ref57"></nolink> <nolink nlid="nl38" bibid="bib33" firstref="ref61"></nolink> <nolink nlid="nl39" bibid="bib11" firstref="ref62"></nolink> <nolink nlid="nl40" bibid="bib22" firstref="ref67"></nolink> <nolink nlid="nl41" bibid="bib46" firstref="ref73"></nolink> <nolink nlid="nl42" bibid="bib37" firstref="ref76"></nolink> <nolink nlid="nl43" bibid="bib14" firstref="ref79"></nolink> <nolink nlid="nl44" bibid="bib32" firstref="ref82"></nolink> <nolink nlid="nl45" bibid="bib30" firstref="ref84"></nolink>
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  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Handheld+Devices%22">Handheld Devices</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunications%22">Telecommunications</searchLink><br /><searchLink fieldCode="DE" term="%22Measures+%28Individuals%29%22">Measures (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Attention%22">Attention</searchLink><br /><searchLink fieldCode="DE" term="%22Validity%22">Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior%22">Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/acp.4034
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0888-4080<br />1099-0720
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Smartphones are a ubiquitous part of many people's lives, but little is known about their impact on everyday thought processes. Here we introduce the "spontaneous smartphone checking scale" (SSCS)--which measures the tendency to direct attention toward one's smartphone, unpreceded by external prompts (e.g., notifications, or alerts) and with no specific conscious goal in mind, as a parallel to mind-wandering directed toward internal thoughts. The SSCS showed good psychometric properties and construct validity. It separated from measures of daydreaming and mind-wandering by not loading on dimensions related to self-consciousness, reflection, and rumination, but instead loading highly on a factor associated with other aspects of digital communication and concerns about public appearance on social media. This suggests that spontaneous smartphone checking serves different mental and social functions than internally generated spontaneous thought processes. We discuss possible long-term effects of spontaneous smartphone checking taking up time for internally generated spontaneous thoughts.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1363094
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1363094
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/acp.4034
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 147
    Subjects:
      – SubjectFull: Handheld Devices
        Type: general
      – SubjectFull: Telecommunications
        Type: general
      – SubjectFull: Measures (Individuals)
        Type: general
      – SubjectFull: Attention
        Type: general
      – SubjectFull: Validity
        Type: general
      – SubjectFull: Psychometrics
        Type: general
      – SubjectFull: Behavior
        Type: general
      – SubjectFull: Cognitive Processes
        Type: general
    Titles:
      – TitleFull: Digital Daydreaming: Introducing the Spontaneous Smartphone Checking Scale
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Berntsen, Dorthe
      – PersonEntity:
          Name:
            NameFull: Hoyle, Rick H.
      – PersonEntity:
          Name:
            NameFull: Munkholm Møller, Daniel
      – PersonEntity:
          Name:
            NameFull: Rubin, David C.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0888-4080
            – Type: issn-electronic
              Value: 1099-0720
          Numbering:
            – Type: volume
              Value: 37
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Applied Cognitive Psychology
              Type: main
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