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Cited by 54Personal Information Management and User BehaviorImpact of Technology on AdolescentsNeural and Behavioral Psychology Studies

Emotion-related impulsivity moderates the cognitive interference effect of smartphone availability on working memory

Open access
Canale, Natale, Vieno, Alessio, Doro, Mattia, Rosa Mineo, Erika, Marino, Claudia, Billieux, Joël·2019·Scientific Reports
DOI 10.1038/s41598-019-54911-7PMC PMC6898282
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Abstract

Although recent studies suggest that the mere presence of a smartphone might negatively impact on working memory capacity, fluid intelligence, and attentional processes, less is known about the individual differences that are liable to moderate this cognitive interference effect. This study tested whether individual differences in emotion-related impulsivity traits (positive urgency and negative urgency) moderate the effect of smartphone availability on cognitive performance. We designed an experiment in which 132 college students (age 18–25 years) completed a laboratory task that assessed visual working memory capacity in three different conditions: two conditions differing in terms of smartphone availability (smartphone turned off and visible, smartphone in silent mode and visible) and a condition in which the smartphone was not available and was replaced by a calculator (control condition). Participants also completed self-reports that assessed their thoughts after the task performance, positive/negative urgency, and problematic smartphone use. The results showed that participants with higher positive urgency presented increased cognitive interference (reflected by poorer task performance) in the “silent-mode smartphone” condition compared with participants in the “turned-off smartphone” condition. The present study provides new insights into the psychological factors that explain how smartphone availability is liable to interfere with high-level cognitive processes.

AI snapshot

Written from the paper’s full text.

TL;DR

In a lab experiment with 120 college students, smartphone availability affected visual working memory capacity, and this cognitive interference was moderated by positive urgency but not negative urgency. Higher positive urgency was linked to poorer working memory in the silent-mode smartphone condition than in the turned-off smartphone condition, especially on the most difficult task set size.

Key findings

  • Positive urgency moderated the effect of smartphone condition on visual working memory: condition × positive urgency interaction χ²(2) = 7.22, p = 0.03, d = 0.51; the model including this interaction best fitted the data (AIC = 614.56, Akaike weight = 0.59).
  • Participants higher in positive urgency performed worse in the silent-mode smartphone condition than in the turned-off smartphone condition (χ²(1) = 6.42, p = 0.03, d = 0.49); overall, silent-mode vs. turned-off performance showed B = 0.78, 95% CI [0.15, 1.41], t = 2.05, p = 0.03, d = 0.38.
  • The positive urgency × condition effect was significant only at the most difficult set size (four squares: F(1,114) = 8.36, p = 0.01), not at set size 3 (p = 0.08) or set size 2 (p = 0.07).
  • Negative urgency did not interact with condition; problematic smartphone use was not significantly associated with task performance (χ²(1) = 0.68, p = 0.40), and no differences were found between calculator and turned-off conditions (p = 0.32) or calculator and silent-mode conditions (p = 0.22).

Methods

  • Experimental laboratory study: 132 college students aged 18–25 were recruited; final sample was 120 (65% female, Mage = 22.73, SD = 1.67) after exclusions. Participants were randomly assigned to turned-off smartphone (n = 40), silent-mode smartphone (n = 41), or calculator control (n = 39).
  • Visual working memory was assessed with a single-probe recognition task (240 trials; set sizes of two, three, or four coloured squares; Cowan’s K). Self-reports measured positive urgency and negative urgency (Short UPPS-P), problematic smartphone use (SPAI), and post-task smartphone-related thoughts.
  • Linear mixed-effects models in R (lme4/lmerTest) included condition, positive or negative urgency, their interaction, SPAI as a control, and participant as a random effect; model selection used AIC and Akaike weights, with post hoc tests via the phia package.

Limitations

  • Stated: the convenience sample of college students limits generalizability; self-report measures are partly flawed, especially for potentially stigmatized excessive phone use; emotional states were not manipulated or measured, so explanations involving positive and negative urgency remain tentative; other moderators such as fear of missing out were not tested; and the study was not preregistered.
  • Stated/paper-noted: the calculator condition may not have been an ideal control, because completely restricting smartphone access might have perturbed or distracted participants; the paper suggests future studies not use it as a control condition.
  • Evident: the final sample was predominantly female and restricted to young college students, so the findings may not extend to other age or gender groups.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/s41598-019-54911-7

Cites

83 of 83 references verified0 citation errors · 0 not checkable

Statistics

17 tests recomputed · 0 with the reported and recomputed p on opposite sides of .05

Claims the paper makes

0 of 53 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Participants performed worse in the silent-mode smartphone condition than in the turned-off smartphone condition.

    “a closer inspection of the results for condition indicated that participants performed worse in the silent-mode smartphone condition (B = 0.78, 95% CI [0.15, 1.41], t = 2.05, p = 0.03, d = 0.38) than did participants in the turned-off smartphone condition”
    Quote in the paperSubstantial claim
  • Findingown data

    The model with the condition × positive urgency interaction term (M4) best fitted the data, with a probability of being the best of 0.59.

    “As the AIC selection method indicated, the model with the condition × positive urgency interaction term (M4) best fitted the data (Table 2), with a probability of being the best of 0.59.”
    Quote in the paperSubstantial claim
  • Findingown data

    Participants with higher positive urgency presented increased cognitive interference (poorer task performance) in the silent-mode smartphone condition compared with the turned-off smartphone condition.

    “The results showed that participants with higher positive urgency presented increased cognitive interference (reflected by poorer task performance) in the “silent-mode smartphone” condition compared with participants in the “turned-off smartphone” condition.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Lower performance on the VWM task in a specific experimental condition indicates cognitive interference from smartphone availability.
  • Findingown data

    Participants with higher positive urgency had poorer task performance in the silent-mode smartphone condition (high availability) than did participants in the turned-off smartphone condition (low availability).

    “participants with higher positive urgency had poorer task performance in the silent-mode smartphone condition (high availability) than did participants in the turned-off smartphone condition (low availability)”
    Quote in the paperSubstantial claim
  • Findingown data

    No differences were found between participants in the calculator condition and those in the turned-off smartphone condition (p = 0.32).

    “no differences were found between participants in the calculator condition and those in the turned-off smartphone condition (p = 0.32)”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 33
  • May combine two claims. 22

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Positive correlations were observed between negative urgency and positive urgency (r = 0.59), negative urgency and SPAI (r = 0.28), and positive urgency and SPAI (r = 0.38).

    “In particular, positive correlations were observed between negative urgency and positive urgency (r = 0.59; p < 0.001), negative urgency and SPAI (r = 0.28; p = 0.002), and positive urgency and SPAI (r = 0.38; p < 0.001).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The magnitude of correlation coefficients was relatively modest, ranging from 0.28 to 0.59.

    “The magnitude of correlation coefficients was relatively modest, ranging from 0.28 to 0.59.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The final sample comprised 120 participants (65% females, Mage = 22.73; SDage = 1.67).

    “Thus, the final sample comprised 120 participants (65% females, Mage = 22.73; SDage = 1.67).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In model M4, problematic smartphone use and positive urgency were not significantly associated with task performance.

    “Regarding this model (M4), problematic smartphone use (SPAI score, χ2 (1) = 0.68, p = 0.40) and positive urgency (χ2 (1) = 1.62, p = 0.20) were not significantly associated with task performance.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Smartphone availability had a detrimental effect on task performance only when devices were turned on (in silent mode, high availability) and not when they were turned off (low availability).

    “we found that smartphone availability had a detrimental effect on task performance only when these devices were turned on (in silent mode, high availability) and not when they were turned off (low availability)”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The effect of positive urgency in interaction with condition (silent-mode vs turned-off) on task performance was statistically significant only in the most difficult part of the task (set size = 4) (F(1,114)=8.36, p=0.01), but not for set size = 3 (p=0.08) or set size = 2 (p=0.07).

    “the effect of positive urgency in interaction with condition (silent-mode smartphone condition vs. turned-off smartphone condition) on task performance was statistically significant only in the most difficult part of the task (set size = 4) (F (1,114) = 8.36, p = 0.01), but not for set size = 3 (p = 0.08) or set size = 2 (p = 0.07)”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Positive and negative urgency are affect-related impulsivity traits that play a crucial role in addictive-like behaviours and are strong trans-diagnostic predictors of psychopathological symptoms.

    “Positive and negative urgency are affect-related impulsivity traits that play a crucial role in addictive-like behaviours41–44 and also constitute strong trans-diagnostic predictors of psychopathological symptoms (for a meta-analysis, see45).”
    Quote in the paperSubstantial claim0 of 5 sources checked
    • cites [41] Canale, N., Vieno, A., Bowden-Jones, H. & Billieux, J. The benefits of using the UPPS model of impulsivity rather than the Big Five when assessing the relationship between personality and problem gambling. Addiction. 112, 372–373 (2017). source

      Not checked in the free run.

    • cites [42] Thomsen, R. ømer et al. Impulsivity traits and addiction-related behaviors in youth. J. Behav. Addict. 7, 317–330 (2018). source

      Not checked in the free run.

    • cites [43] Stautz, K., Dinc, L. & Cooper, A. J. Combining trait models of impulsivity to improve explanation of substance use behaviour. Eur. J. Pers. 31, 118–132 (2017). source

      Not checked in the free run.

    • cites [44] Wéry, A., Deleuze, J., Canale, N. & Billieux, J. Emotionally laden impulsivity interacts with affect in predicting addictive use of online sexual activity in men. Compr. Psychiat. 80, 192–201 (2018). source

      Not checked in the free run.

    • cites [45] Berg, J. M., Latzman, R. D., Bliwise, N. G. & Lilienfeld, S. O. Parsing the heterogeneity of impulsivity: A meta-analytic review of the behavioral implications of the UPPS for psychopathology. Psychol. Assessment. 27, 1129–1146 (2015). source

      Not checked in the free run.

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    Premisecitation

    The mere presence of a smartphone (turned off) has a negative impact on working memory capacity, fluid intelligence, and attentional processes.

    “Moreover, the mere presence of a smartphone (turned off) has been found to have a negative impact on working memory capacity, fluid intelligence, and attentional processes21,22.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [21] Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. J. Assoc. Consum. Res. 2, 140–154 (2017). source

      Not checked in the free run.

    • cites [22] Thornton, B., Faires, A., Robbins, M. & Rollins, E. The mere presence of a cell phone may be distracting: Implications for attention and task performance. Soc. Psychol. 45, 479–488 (2014). source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    The effect of smartphone presence/availability during cognitive performance is moderated by mobile phone dependence, Internet use/attachment, and nomophobia.

    “Recent research also suggests that the effect of smartphone presence/availability during cognitive performance is moderated by mobile phone (psychological) dependence21, Internet use/attachment30, and nomophobia (i.e., the fear of being without access to one’s cell phone16), all of these constructs being assessed with self-report scales.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [21] Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. J. Assoc. Consum. Res. 2, 140–154 (2017). source

      Not checked in the free run.

    • cites [30] Ito, M. & Kawahara, J. I. Effect of the presence of a mobile phone during a spatial visual search. Jpn Psychol Res. 59, 188–198 (2017). source

      Not checked in the free run.

    • cites [16] Mendoza, J. S., Pody, B. C., Lee, S., Kim, M. & McDonough, I. M. The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia. Comput. Hum. Behav. 86, 52–60 (2018). source

      Not checked in the free run.

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    Premisecitation

    The cognitive interference effect impairs the ability to voluntarily inhibit high-priority yet task-irrelevant habits such as checking a smartphone.

    “It has been proposed that this “cognitive interference effect” impairs the ability to voluntarily inhibit high-priority yet task-irrelevant habits such as checking a smartphone19,21,23.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [19] Clapp, W. C., Rubens, M. T. & Gazzaley, A. Mechanisms of working memory disruption by external interference. Cereb. Cortex. 20, 859–872 (2009). source

      Not checked in the free run.

    • cites [21] Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. J. Assoc. Consum. Res. 2, 140–154 (2017). source

      Not checked in the free run.

    • cites [23] Lavie, N., Hirst, A., De Fockert, J. W. & Viding, E. Load theory of selective attention and cognitive control. J. Exp. Psychol. Gen. 133, 339–354 (2004). source

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    Premisecitation

    Smartphone availability worsens performance on working memory (OSpan) and fluid intelligence (Raven) tasks.

    “Their data showed that the availability of the participants’ smartphones worsened performances on two tasks: the Automated Operation Span task (OSpan, a prominent measure of working memory capacity27) and a 10-item subset of Raven’s Standard Progressive Matrices (a nonverbal measure of fluid intelligence28).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21] Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. J. Assoc. Consum. Res. 2, 140–154 (2017). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Among impulsivity facets, urgency is most strongly related to mobile phone addictive use and related negative consequences.

    “Among impulsivity facets, urgency was shown to be the most strongly related to mobile phone addictive use and related negative consequences35,36.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [35] Billieux, J., Van der Linden, M. & Rochat, L. The role of impulsivity in actual and problematic use of the mobile phone. Appl. Cognitive Psych. 22, 1195–1210 (2008). source

      Not checked in the free run.

    • cites [36] Contractor, A. A., Weiss, N. H., Tull, M. T. & Elhai, J. D. PTSD’s relation with problematic smartphone use: Mediating role of impulsivity. Comput. Hum. Behav. 75, 177–183 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Premiseown data

    Only smartphone location, not smartphone power, affected performance on OSpan and Go/No-Go tasks.

    “Results indicated that only smartphone location (but not smartphone power, either main effect or in interaction with location) affected performance on two tasks: OSpan (as in the first experiment) and a Go/No-Go task (a measure of inhibitory control29).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [21] Ward, A. F., Duke, K., Gneezy, A. & Bos, M. W. Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity. J. Assoc. Consum. Res. 2, 140–154 (2017). source

      Not checked in the free run.

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    Study design and conductown data

    Four participants were excluded because they did not complete the questionnaires.

    “In addition, four participants were excluded because they did not complete the questionnaires.”
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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Cronbach's alpha was 0.75 for positive urgency and 0.80 for negative urgency.

    “Cronbach’s alpha was 0.75 (95% confidence interval [CI] [0.66, 0.81]) for positive urgency and 0.80 (95% CI [0.73, 0.85]) for negative urgency.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    No multicollinearity issues were detected for the LMMs; all predictors had tolerance values of at least 0.60 and VIF values below 1.67.

    “No multicollinearity issues were detected for the LMMs. All predictors had tolerance values of at least 0.60 and VIF values below 1.67.”
    Quote in the paperNot a substantial claim

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    Study design and conductnone given

    The institutional review board at the University of Padova gave ethical approval for the study.

    “The institutional review board at the University of Padova gave ethical approval for the study (protocol number: 2432).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Eight participants were a priori excluded for color recognition problems, smartphone lighting up, or chance performance.

    “Eight participants were a priori excluded: two participants reported colour recognition problems, three participants’ smartphones lit up during the task, and in three cases, the performance was not distinguishable from chance (less than 60% correct answers54).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [54] Dien, J., Brian, E. S., Molfese, D. L. & Gold, B. T. Combined ERP/fMRI evidence for early word recognition effects in the posterior inferior temporal gyrus. Cortex. 49, 2307–2321 (2013). source

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    Study design and conductown data

    Random assignment was used to assign participants to the three smartphone availability conditions.

    “We manipulated smartphone availability by randomly assigning participants to one of the three conditions: (1) turned-off smartphone (low availability), (2) silent smartphone (high availability), and (3) calculator (no availability, control condition).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The scales were selected to prioritize instruments validated in Italian.

    “The scales included in the present study were selected to prioritize instruments that have been validated in the Italian language (adapted via a traditional translation and back-translation procedure).”
    Quote in the paperNot a substantial claim

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    Study design and conductcitation

    The experiment was systematically conducted between 9:00 am and 1:30 pm to prevent individual differences in task performance.

    “To prevent individual differences in task performance, we systematically conducted the experiment between 9:00 am and 1:30 pm55–57.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [55] May, C. P. & Hasher, L. Synchrony effects in inhibitory control over thought and action. J. Exp. Psychol. Hum. 24, 363–379 (1998). source

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    • cites [56] May, C. P., Hasher, L. & Stoltzfus, E. R. Optimal time of day and the magnitude of age differences in memory. Psychol. Sci. 4, 326–330 (1993). source

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    • cites [57] Rowe, G., Hasher, L. & Turcotte, J. Short article: Age and synchrony effects in visuospatial working memory. Q. J. Exp. Psychol. 62, 1873–1880 (2009). source

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    VWM capacity correlates with visual attention and fluid intelligence.

    “VWM capacity is known to correlate with some important aspects of human cognition, such as visual attention and fluid intelligence51.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [51] Unsworth, N., Fukuda, K., Awh, E. & Vogel, E. K. Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive. Psychol. 71, 1–26 (2014). source

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    Study design and conductown data

    Cronbach's alpha was 0.90 for SPAI.

    “Cronbach’s alpha was 0.90 (95% CI [0.88, 0.93]).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    The three groups did not differ at baseline in age, education, gender, negative urgency, positive urgency, problematic smartphone use, and smartphone-related thoughts.

    “The three groups did not differ in terms of age, education, and gender distribution, nor regarding negative urgency and positive urgency, problematic smartphone use, and smartphone-related thoughts.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Individuals with high positive urgency have more difficulty in inhibiting mobile phone use when it is available, as mobile phone use involves highly automatized habits.

    “it might be that individuals with high positive urgency have more difficulty in inhibiting mobile phone use when it is available, as mobile phone use (e.g., checking email or notifications) involves highly automatized habits76,77”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [76] Oulasvirta, A., Rattenbury, T., Ma, L. & Raita, E. Habits make smartphone use more pervasive. Pers. Ubiquit. Comput. 16, 105–114 (2012). source

      Not checked in the free run.

    • cites [77] Van Deursen, A. J., Bolle, C. L., Hegner, S. M. & Kommers, P. A. Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Comput. Hum. Behav. 45, 411–420 (2015). source

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    Interpretationown data

    Smartphones in silent mode might promote cognitive interference in an automatic way (without conscious monitoring) given that participants in the silent-mode smartphone condition did not report more smartphone-related thoughts in the post-task questionnaire than did participants in the other two conditions.

    “It is plausible that smartphones in silent mode might promote cognitive interference in an automatic way (i.e., without conscious monitoring) given that participants in the silent-mode smartphone condition did not report more smartphone-related thoughts in the post-task questionnaire (see Measures section) than did participants in the other two conditions.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationreasoning

    Impaired performance in the task used to assess attentional and VWM capacities is related to incoming notifications (or the possibility of receiving a notification), implying that participants in the silent-mode smartphone condition were perturbed by possible missed notifications or messages.

    “It is thus possible that impaired performance in the task used to assess attentional and VWM capacities is related to incoming notifications (or the possibility of receiving a notification), implying that participants in the silent-mode smartphone condition were perturbed by possible missed notifications or messages.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    The calculator condition is not directly comparable to the other two conditions (which differ only in terms of availability), which makes the interpretation of the results related to this condition uncertain.

    “It is thus possible that the calculator condition is not directly comparable to the other two conditions (which differ only in terms of availability), which makes the interpretation of the results related to this condition uncertain.”
    Quote in the paperSubstantial claim

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    Study design and conductown data

    Participants gave informed consent.

    “Participants were informed about the details of the study and gave their informed consent.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Adolescents and young adults have a strong feeling of dependence on their mobile phone and these technological devices are even stronger than natural reinforcers such as food.

    “previous studies showed that adolescents and young adults have a strong feeling of dependence on their mobile phone74 and that these technological devices are even stronger than natural reinforcers such as food75”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [74] Lopez-Fernandez, O. et al. Self-reported dependence on mobile phones in young adults: A European cross-cultural empirical survey. J. Behav. Addict. 6, 168–177 (2017). source

      Not checked in the free run.

    • cites [75] O’Donnell, S. & Epstein, L. H. Smartphones are more reinforcing than food for students. Addict. Behav. 90, 124–133 (2019). source

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    Interpretationcitation

    This result is consistent with previous studies that found heightened cognitive interference in situations characterized by a greater demand on attentional and cognitive resources.

    “which is consistent with the results of previous studies that found heightened cognitive interference in situations characterized by a greater demand on attentional and cognitive resources22,80”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [22] Thornton, B., Faires, A., Robbins, M. & Rollins, E. The mere presence of a cell phone may be distracting: Implications for attention and task performance. Soc. Psychol. 45, 479–488 (2014). source

      Not checked in the free run.

    • cites [80] Schneider, W. & Shiffrin, R. M. Controlled andautomatic human information processing: I Detection, search, and attention. Psychol. Rev. 84, 1–66 (1977). source

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  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The existing literature highlights the link between negative urgency and problematic smartphone use.

    “The existing literature highlights the link between negative urgency and problematic smartphone use;35,36”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [35] Billieux, J., Van der Linden, M. & Rochat, L. The role of impulsivity in actual and problematic use of the mobile phone. Appl. Cognitive Psych. 22, 1195–1210 (2008). source

      Not checked in the free run.

    • cites [36] Contractor, A. A., Weiss, N. H., Tull, M. T. & Elhai, J. D. PTSD’s relation with problematic smartphone use: Mediating role of impulsivity. Comput. Hum. Behav. 75, 177–183 (2017). source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    A recent meta-analysis found that the effect size for negative urgency with response inhibition was robust in a clinical sample (weighted mean r = .34) but was very small in a student and a community sample (weighted mean r = .12).

    “A recent meta-analysis45 found that the effect size for negative urgency with response inhibition was robust in a clinical sample (weighted mean r = . 34) but was very small in a student and a community sample (weighted mean r = . 12).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [45] Berg, J. M., Latzman, R. D., Bliwise, N. G. & Lilienfeld, S. O. Parsing the heterogeneity of impulsivity: A meta-analytic review of the behavioral implications of the UPPS for psychopathology. Psychol. Assessment. 27, 1129–1146 (2015). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Positive urgency has notably been related to increased difficulty in inhibiting prepotent responses.

    “Considering that positive urgency has notably been related to increased difficulty in inhibiting prepotent responses47”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [47] Johnson, S. L., Tharp, J. A., Peckham, A. D., Sanchez, A. H. & Carver, C. S. Positive urgency is related to difficulty inhibiting prepotent responses. Emotion. 16, 750–759 (2016). source

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  • Classified as probably not a substantial claim.

    Premisecitation

    Two recent studies found that trait negative urgency is associated with more rash behaviour following a stressful experience.

    “two recent studies found that trait negative urgency is associated with more rash behaviour following a stressful experience82,83”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [82] Canale, N., Rubaltelli, E., Vieno, A., Pittarello, A. & Billieux, J. Impulsivity influences betting under stress in laboratory gambling. Sci. Rep. 7, 1–12 (2017). source

      Not checked in the free run.

    • cites [83] Owens, M. M., Amlung, M. T., Stojek, M. & MacKillop, J. Negative urgency moderates reactivity to laboratory stress inductions. J. Abnorm. Psychol. 127, 385–393 (2018). source

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationcitation

    Individuals with high negative urgency may display impaired response inhibition related to smartphone availability only in emotional contexts in which negative affect is experienced, or during the inhibition of negative stimuli.

    “It is possible that individuals with high negative urgency display impaired response inhibition related to smartphone availability only in emotional contexts in which negative affect is experienced, or during the inhibition of negative stimuli81.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [81] Chester, D. S. et al. How do negative emotions impair self-control? A neural model of negative urgency. NeuroImage. 132, 43–50 (2016). source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Smartphone reinforcing efficacy is associated with positive (reward related) use motives.

    “As previous research showed that smartphone reinforcing efficacy is associated with positive (reward related) use motives75”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [75] O’Donnell, S. & Epstein, L. H. Smartphones are more reinforcing than food for students. Addict. Behav. 90, 124–133 (2019). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationreasoning

    The cognitive interference generated by the simple availability of a smartphone may have implications in various contexts and situations (e.g., driving, performance in school, and productivity in the workplace).

    “The cognitive interference generated by the simple availability of a smartphone may have implications in various contexts and situations (e.g., driving, performance in school, and productivity in the workplace).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The study relied on self-reported measures, which are known to be at least partly flawed, especially when it comes to potentially stigmatized behaviours such as excessive mobile phone use.

    “we relied on self-reported measures, which are known to be at least partly flawed, especially when it comes to potentially stigmatized behaviours such as excessive mobile phone use”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationcitation

    Other factors, such as specific psychological factors (e.g., fear of missing out or "FOMO"), may moderate the cognitive interference effect in various ways.

    “it is possible that other factors, such as specific psychological factors (e.g., fear of missing out or “FOMO”84), moderate the cognitive interference effect in various ways”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [84] Wolniewicz, C. A., Tiamiyu, M. F., Weeks, J. W. & Elhai, J. D. Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiat. Res. 262, 618–623 (2018). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The study did not preregister the study hypotheses.

    “we did not preregister the study hypotheses”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    The study did not manipulate emotional states (e.g., via induction) or measure actual affect states, implying that explanations regarding the differential effect of positive and negative urgency remain tentative.

    “the study did not manipulate emotional states (e.g., via induction) or measure actual affect states, implying that our explanations regarding the differential effect of positive and negative urgency remain tentative”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Recent research found that negative urgency is associated with problematic smartphone use, showing that this risky behaviour is more likely to occur in the context of intense negative emotions among people who are characterized by post-traumatic stress disorder symptoms.

    “recent research found that negative urgency is associated with problematic smartphone use36, showing that this risky behaviour is more likely to occur in the context of intense negative emotions among people who are characterized by post-traumatic stress disorder symptoms.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [36] Contractor, A. A., Weiss, N. H., Tull, M. T. & Elhai, J. D. PTSD’s relation with problematic smartphone use: Mediating role of impulsivity. Comput. Hum. Behav. 75, 177–183 (2017). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    The present study adds to previous research by improving knowledge about how smartphone availability competes with high-level cognitive processes and thus creates a cognitive interference effect.

    “the present study adds to previous research by improving our knowledge about how smartphone availability competes with high-level cognitive processes and thus creates a cognitive interference effect”
    Quote in the paperNot a substantial claim
44 of 44

  • The paper relies on this without support.

    Lower performance on the VWM task in a specific experimental condition indicates cognitive interference from smartphone availability.

    “Given the sensitivity of this measure, we reasoned that it is a relevant variable to test the postulated cognitive interference effect. Indeed, if performance on the VWM task is lower in a specific experimental condition, this would mean that the difference observed can be linked to a cognitive interference effect of smartphone availability.”

  • The paper relies on this without support.

    The three smartphone conditions (silent-mode, turned-off, calculator) validly manipulate smartphone availability as intended (high, low, no availability).

    “participants were exposed to various degrees of availability of their smartphones (high availability, low availability, no availability)”

  • The paper relies on this without support.

    The VWM task validly measures visual working memory capacity and attentional processes.

    “a task involving VWM capacity and attentional processes”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Statistics that don’t add up

Each reported p-value recomputed from its test statistic and degrees of freedom.

  • Inconsistent p-value: χ2 (2) = 5.12, p = .07

    Minor

    The paper reports p = .07 here; recomputing from the test statistic and its degrees of freedom gives p = .077. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .07 · recomputed p = .077

  • Inconsistent p-value: χ2 (1) = 0.68, p = .40

    Minor

    The paper reports p = .4 here; recomputing from the test statistic and its degrees of freedom gives p = .410. The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p = .4 · recomputed p = .410

2 of 2

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Doesn’t add upχ²(1) = 0.68reported p = .4 · recomputed p = .410

    “χ2 (1) = 0.68, p = .40”

  • Doesn’t add upχ²(2) = 5.12reported p = .07 · recomputed p = .077

    “χ2 (2) = 5.12, p = .07”

  • Not confirmedχ²(1) = 6.42reported p = .03 · recomputed p = .011

    “χ2 (1) = 6.42, p = .03”

  • Not confirmedχ²(1) = 1.28reported p = .27 · recomputed p = .258

    “χ2 (1) = 1.28, p = .27”

  • Not confirmedχ²(1) = 2.51reported p = .24 · recomputed p = .113

    “χ2 (1) = 2.51, p = .24”

  • Consistentχ²(2) = 0.74reported n.s. · recomputed p = .691

    “χ2(2) = 0.74, ns”

  • ConsistentF(2, 117) = 0.35reported n.s. · recomputed p = .705

    “F(2,117) = 0.35, ns”

  • ConsistentF(2, 117) = 0.43reported n.s. · recomputed p = .652

    “F(2,117) = 0.43, ns”

  • ConsistentF(2, 117) = 0.17reported n.s. · recomputed p = .844

    “F(2,117) = 0.17, ns”

  • ConsistentF(2, 117) = 1.13reported n.s. · recomputed p = .327

    “F(2,117) = 1.13, ns”

  • ConsistentF(2, 117) = 0.44reported n.s. · recomputed p = .645

    “F(2,117) = 0.44, ns”

  • Consistentχ²(2) = 3.7reported n.s. · recomputed p = .157

    “χ2(2) = 3.70, ns”

  • Consistentχ²(2) = 1.96reported n.s. · recomputed p = .375

    “χ2(2) = 1.96, ns”

  • Consistentχ²(2) = 3.8reported n.s. · recomputed p = .150

    “χ2(2) = 3.80, ns”

  • Consistentχ²(1) = 1.62reported p = .2 · recomputed p = .203

    “χ2 (1) = 1.62, p = .20”

  • Consistentχ²(2) = 7.22reported p = .03 · recomputed p = .027

    “χ2 (2) = 7.22, p = .03”

  • ConsistentF(1, 114) = 8.36reported p = .01 · recomputed p = .005

    “F (1,114) = 8.36, p = .01”

    The paper prints p at a floor (such as p < .001)

17 of 17

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Self-check results appear here once an independent check has confirmed them.

Cites

Flagged first, then by citations

1 of the 84 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Raven, J. C. Raven’s progressive matrices and vocabulary scales (Oxford pyschologists Press, 1998).

Cited by

Sorted by citations

Related

Authors
Canale, N., Vieno, A., Doro, M., Rosa Mineo, E., Marino, C., & Billieux, J.
Affiliations
  • University of Padua (IT)
  • University of Luxembourg (LU)
Corresponding author
Canale, Natale
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2019-12-06
Volume
9
Issue
1
Pages
18519-18519
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-019-54911-7
PMC
PMC6898282
OpenAlex
W2993629947
Semantic Scholar
b61415bf84cb508f08d2bf917524a943c64d2ffe
Cited by
50
References
84
Citations by year
2026: 1 · 2025: 8 · 2024: 9 · 2023: 9 · 2022: 11 · 2021: 5 · 2020: 7
FWCI
6.80
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • SERVAL (Université de Lausanne) (publishedVersion, cc-by)
  • IRIS (submittedVersion, cc-by)
  • Open Repository and Bibliography (University of Luxembourg) (submittedVersion, cc-by-nc-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion, cc-by)
Funders
Università degli Studi di Padova
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
working memory capacity, emotion-related impulsivity, positive urgency, negative urgency, cognitive interference, individual differences, smartphone addiction, attentional interference, fluid intelligence, university students
MeSH terms
Smartphone, Adolescent, Adult, Attention, Cognition, Emotions, Female, Humans, Impulsive Behavior, Individuality, Male, Memory, Short-Term, Students, Young Adult, Self Report

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-08.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-08.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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