Author (s)

Smartphone use scale

Anxiety scale

Findings

Boumosleh, et al. [15]

Smartphone addiction inventory (SPAI) [45]

Generalized anxiety disorder-7 (GAD-7) [46]

Anxiety was an independent positive predictive factor of smartphone addiction. Anxiety (mean SPAI score: Anxious 59.04 vs. non-anxious 54.62, p = 0.028) The SPAI score was found to be significantly higher for anxiety in a multiple linear regression with adjustment and the total variance explained by the model was 21% for anxiety (Std. B = 0.122, p = 0.034).

Cheever, et al. [16]

Wireless mobile device (WMD) use scale [47]

State-trait anxiety inventory (STAI) [48]

Anxiety was shown to increase over time in participants without their devices regardless of its location (p < 0.01). Heavy users experienced the most stress by the absence of the mobile device (p = 0.01).

Chen, et al. [17]

Mobile phone addiction scale-xiong (MPAS-X) [49]

Self-consciousness scale - social anxiety subscale [50]

In a regression model, smartphone addiction was a significant predictor of anxiety (B = 0.50, t = 3.27, p < 0.01). However, when the model was controlled for interpersonal problems, the level of addiction to smartphones had no significant effect on anxiety (B = 0.24, t = 1.54, p > 0.05).

Chen, et al. [18]

Smartphone addiction scale-short version (SAS-SV) [51]

Self-rating anxiety scale-zung (SAS-Z) [52]

Smartphone addiction rate was 29.8% (30.3% in males, 29.3% in females). In a multivariate logistic regression analysis, male students with comorbid anxiety were more likely to have smartphone addiction (OR = 1.78, 95% CI 1.09-2.89, p < 0.05). Female students with anxiety were also more likely to have smartphone addiction (OR = 2.31, 95% CI 1.18-4.51, p < 0.05).

Choi, et al. [19]

Smartphone addiction scale
(SAS) [53]

State-trait anxiety inventory (STAI) [48]

In a stepwise multiple regression analysis, higher anxiety was found to be independently associated with higher levels of smartphone addiction (Std. B = 0.224, t = 4.426, p < 0.01).

Demirci, et al. [21]

Smartphone addiction scale (SAS) [53]

Beck anxiety inventory (BAI) [54]

Smartphone addiction scores were significantly higher in females (p < 0.01) and anxiety (p < 0.01), depression (p < 0.01). Daytime dysfunction (p < 0.01) as measured by the PSQI score was higher in those that had high use of smartphones compared to the low use group. In a linear regression model, anxiety was significantly associated with smartphone addiction severity (Std. B = 0.094, t = 3.084, p < 0.01).

Eyvazlou, et al. [23]

Internet over-use scale and cell- phone over-use scale (IOS/COS) [55]

General health questionnaire 28-anxiety and insomnia subscale (GHQ-28) [56]

A multivariate regression analysis investigating cell phone overuse showed significant effects on social dysfunction (p < 0.05) and depression (p = 0.01) but showed no significant impact on anxiety (p > 0.05). However, this study did look at sleep quality and found that effects on sleep quality also had an impact on the anxiety and depression scales (p < 0.01).

Gao, et al. [25]

Mobile phone addiction index (MPAI) [57]

Depression anxiety and
stress scale (DASS-21) [58]

Participants were more likely to have alexithymia (inability to identify or show feelings) which affected mobile phone addiction (p < 0.01), depression (p < 0.01), stress (p < 0.01), and anxiety (p < 0.01). Depression and anxiety significantly affected mobile phone addiction (p < 0.01). Inclusion of anxiety in the model increased the explanation of mobile phone addiction by 10.3%.

Hawi, et al. [27]

Smartphone addiction scale (SAS) [53]

Beck anxiety inventory (BAI) [54]

The odds of having anxiety in undergraduate students addicted to their smartphones was 4.7 times higher than non-addicted students (95% CI 1.511-14.659, p = 0.008).

Kim, et al. [28]

Smartphone addiction proneness scale (SAPS) [59]

Experiences in close relationships-revised-Korean [60]

The path from attachment anxiety to loneliness was significant (B = 0.55, t = 5.99). The total effect of attachment avoidance on smartphone addiction was significant (p < 0.01). The total effect of attachment anxiety and smartphone addiction was also significant (p < 0.01).

Kim, et al. [29]

Smartphone addiction proneness scale (SAPS) [59]

Investigator-developed

Smartphone overuse was associated with psychotic anxiety by a twofold increase (p < 0.05) when compared to those with psychological anxiety. Students who reported overuse of smartphones were more likely to report their health was “not good” (OR 1.98, 95% CI 1.22-3.21).

Lee, et al. [31]

Questionnaire on mobile
telephone dependency [61]

Self-Rating anxiety scale-zung (SAS-Z) [52]

The amount of time on smartphones and the purpose of use affected dependency upon smartphones in both men and women. Daily use time and dependency were directly correlated. Smartphone dependency was directly correlated with risk of abnormal anxiety in men and women and increased by 10.1% and 9.2%, respectively (p < 0.01).

Lepp, et al. [32]

Investigator-developed

Beck anxiety inventory
(BAI) [54]

The median cell phone use per day was 278 minutes with a median of 76 texts sent per day. In a regression analysis, cell phone use was positively related to anxiety (B = 0.10, p < 0.05).

Long, et al. [33]

Problematic cellular phone use
questionnaire (PCPUQ) [62]

Self-rating anxiety
scale-zung (SAS-Z) [52]

Anxiety and depression were collapsed into a single variable “emotional symptoms”. Through regressional analysis, emotional symptoms were identified as a risk factor for problematic use (p < 0.05).

Mok, et al. [34]

Smartphone addiction scale (SAS) [53]

State-trait anxiety
inventory (STAI) [48]

Mean anxiety scores were significantly higher in female respondents (45.69 ± 9.42) vs. male respondents (41.60 ± 9.68), which was significant (p < 0.01). Smartphone addiction scores were also higher in female respondents (74.67 ± 25.50) vs. male respondents (59.65 ± 21.08), which was significant (p < 0.01). In latent class analysis, smartphone addiction was significantly accompanied by higher levels of anxiety (F = 22.55, p < 0.01). A common trend for psychosocial trait factors was found for both sexes: Anxiety levels and neurotic personality traits increased with addiction severity levels (p < 0.01).

Panova, et al. [35]

Questionnaire about experiences
related to the internet (CERI) [63]

Mood and anxiety
symptom questionnaire-anxious arousal
subscale (MASQ) [64]

Correlation found between maladaptive mobile phone use and anxiety (r = 0.452, p < 0.01). Study suggests that long term use of mobile phone use as a coping strategy may have a negative impact on mental health.

Saadat, et al. [38]

Investigator-developed

Beck anxiety inventory
(BAI) [54]

A significant correlation was found between mobile phone dependency and anxiety scores (r = 0.190, p = 0.005).

Sapacz, et al. [41]

Mobile phone problem use scale
(PMPU) [65]

State-trait anxiety inventory (STAI) [48]

Self-beliefs related to social anxiety scale (SANX) [66]

In a regression analysis, problematic mobile phone use did not predict state anxiety for any of the experimental conditions, including “taken away” (B = -0.010, t = -0.200, p = 0.842), “salient” (B = -0.025, t = -0.521, p = 0.606, and “hidden” (B = -0.045, t = -0.668, p = 0.509).

Tao, et al. [42]

Self-rating questionnaire for adolescent problematic mobile phone use (SQAPMPU) [67]

Self-rating anxiety scale-zung (SAS-Z) [52]

Higher rates of anxiety symptoms were seen in those with problematic mobile phone use (p < 0.01). Higher rates of psychopathological symptoms, depression, and anxiety symptoms were seen in those with internet addiction (p < 0.01) and poor sleep quality (p < 0.01).