Technological advancement has transformed nearly every aspect of modern life. Nonetheless excessive use of smartphone has become a matter of concern. Adolescents and young adults tend to be more attached or addictive to smartphones and their effects are seen either physically or psychologically. However, there are still no established diagnostic criteria for smartphone addiction in The Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. The present review aimed at looking into the available evidence of personality factors in connection with smartphone use and thereby exploring the role of personality in interventions for smartphone addiction on the ground of theoretical foundation. Findings revealed that high neuroticism was significantly related to excessive use and even predicted problematic use of smartphones. Though studies revealed that extraversion may cause an individual to be inclined to increased smartphone usage, it would not lead to smartphone addiction. Similarly, openness to experience traits showed a slight negative association and were not significant predictors of smartphone addiction, whereas conscientiousness and high agreeableness appeared to be protective factors against its development. Research on the relationship between smartphone addiction and social-emotional distress is still in its early stages, requiring cautious generalization. Since eliminating smartphone use completely is impractical, possible interventions for smartphone addiction linked with personality are recommended.

Intuitive eating is a key focus in health psychology and has been closely linked to negative emotions, particularly among college students. A study examining the protective and risk factors influencing students' intuitive eating could be valuable in helping them manage their weight and improve their emotional well-being. We therefore examined the effects of physical activity and internet addiction. A total of two studies were conducted: a questionnaire survey and an ecological transient assessment. Ultimately, we found that physical activity did not influence students' intuitive eating. However, we found that internet addiction negatively influenced college students' intuitive eating, both in terms of immediate and short-term delayed effects. Using multiple studies, we found that physical activity was not a predictor of intuitive eating and that internet addiction had both immediate and short-term delayed effects on intuitive eating. Furthermore, there was no interaction effect between the two.

Given the insufficient validation of previously imported smartphone addiction scales in China, this study revised and evaluated the Problematic Smartphone Use Scale among Chinese college students (PSUS-C).

We based our research on a national sample comprising 1324 higher education institutions and 130 145 participants. Using cross-sectional data, comprehensive methods were employed to examine validity, reliability and measurement invariance.

The final scale consists of 20 items across four dimensions: withdrawal and loss of control, negative impact, salience behaviors and excessive use. All Heterotrait-Monotrait (HTMT) values were below 0.85, and the lower 90% and upper 95% confidence intervals were also below 0.85, except for factors 1 and 3. The amount of variance (AVE) values were greater than 0.5, composite reliability (ω) values exceeded 0.89 and all factor loadings were above 0.5. The criterion validity was supported as expected: problematic smartphone usage positively correlated with depression (r = 0.451), loneliness (8 items, r = 0.455), loneliness (6 items, r = 0.504), social media use (r = 0.614) and phone usage duration (r = 0.148); and negatively correlated with life satisfaction (r = -0.218) and self-esteem (r = -0.416). Across sex, type of university and place of residence, the measurement invariance performed well, with most changes in root mean square error of approximation (ΔRMSEA), comparative fit index (ΔCFI) and Tucker-Lewis index (ΔTLI) values being less than 0.005, and no indicator showing a difference greater than 0.010.

The Problematic Smartphone Use Scale for College Students (PSUS-C) demonstrated good factor structure, internal consistency, construct validity, discriminant validity and criterion validity. Strict and structural invariance were demonstrated across sex, type of university and place of residence. The PSUS-C has the potential to assess smartphone addiction among Chinese university students.

Social anxiety is an emerging public health issue associated with significant impairment of social functioning during adolescence. Among many determinants of social anxiety, proneness to smartphone addiction may significantly contribute to the development of social anxiety. To cope with the consequential development of social anxiety, adolescent school students may rely on various forms of social support. Particularly in the Middle East, including Jordan, the relationship between proneness to smartphone addiction and adolescent social anxiety is understudied.

To examine the mediating role of social support in the relationship between proneness to smartphone addiction and social anxiety in a sample of adolescent school students.

In this cross-sectional study, 432 adolescents were recruited via a random cluster sample from public schools across three provinces in Jordan. The data were collected face-to-face using the Social Anxiety Scale for Adolescents, the Smartphone Addiction Proneness Scale, and the Multidimensional Scale of Perceived Social Support.

Significantly higher levels of social anxiety were associated with females of lower economic status who reported more gaming hours and higher levels of proneness to smartphone addiction. Familial social support significantly mediated the relationship between proneness to smartphone addiction and social anxiety, controlling for the other covariates in the social anxiety model.

Familial social support reduced the impact of proneness to smartphone addiction on social anxiety. Nurses may supplement treatment for reducing social anxiety in adolescents suffering from proneness to smartphone addiction by fostering sources of familial social support.

College students are disproportionately affected by smartphone addiction, which has been linked to various health impairments, including sleep disorders. This study explores the relationship between smartphone addiction and sleep disorders, with a focus on negative emotions as a mediator and gender as a moderator.

Cluster sampling was used to survey 1056 Chinese college students. The Mobile Phone Addiction Index, Negative Affect Scale, and Sleep Disorder Scale were administered. Versions of SPSS 27.0 and PROCESS macro 4.0 were used for data analysis, employing Models 15 and 4 to examine moderation and mediation, respectively.

A strong direct correlation was identified between smartphone addiction and sleep disorder, with negative emotions mediating this relationship, accounting for 33.7% of the effect. Gender significantly moderated the mediation process, with females demonstrating a greater correlation than males between sleep disorders and negative emotions.

Negative emotions partially mediated smartphone addiction's association with sleep disorder, whereas gender significantly moderated this mediation. These findings underscore the complex dynamics among smartphone addiction, emotional well-being, and sleep among college students.

The theoretical model of smartphone addiction highlights the role of emotional factors in fostering addictive behaviors. However, most research has focused on long-term emotional states and pathologies, often overlooking the immediate effects of daily emotional fluctuations on smartphone usage and their mechanisms.

Our study employed an online survey and a moderated parallel mediation model to explore how daily emotional experiences influence smartphone addiction among college students. We analyzed the mediating roles of anxiety, stress, and depression, and the moderating effect of gender.

Our findings indicate that daily negative emotional experiences were positively correlated with smartphone addiction, with stress serving as a significant mediator in the relationship between both positive and negative emotional experiences and addiction. Interestingly, positive emotional experiences directly increased smartphone addiction risk among female students, but they also significantly reduced stress and depression, especially pronounced in women. Further analysis indicated that positive emotions primarily mitigate addiction through reducing stress, a pathway especially significant in females.

The study not only confirms the substantial impact of emotional experiences on addiction but also deepens our understanding of their mechanisms, underlining the importance of considering the nature of emotional experiences and gender-specific effects in devising prevention and intervention strategies.

This study aims to develop an artificial neural network (ANN) prediction model incorporating random forest (RF) screening ability for predicting the risk of depression in adolescents and identifies key risk factors to provide a new approach for primary care screening of depression among adolescents.

The data were from a large cross-sectional study conducted in China from July to September 2021, enrolling 8635 adolescents aged 10-17 with their parents. We used the Patient health questionnaire (PHQ-9) to rate adolescent depression symptoms, using scales and single-item questions to collect demographic information and other variables. Initial model variables screening used the RF importance assessment, followed by building prediction model using the screened variables through the ANN.

The rate of depression symptoms in adolescents was 24.6%, and the depression risk prediction model was built based on 70% of the training set and 30% of the test set. Ten variables were included in the final prediction model with a model accuracy of 85.03%, AUC of 0.892, specificity of 89.79%, and sensitivity of 70.81%. The top 10 significant factors of depression risk were adolescent rumination, adolescent self-esteem, adolescent mobile phone addiction, peer victimization, care in parenting styles, overprotection in parenting styles, academic pressure, conflict in parent-child relationship, parental rumination, and relationship between parents.

The ANN model based on the RF effectively identifies depression risk in adolescents and provides a methodological reference for large-scale primary screening. Cross-sectional studies and single-item scales limit further improvements in model accuracy.

The incidence of smartphone addiction has been widely studied, but the research on the relationship between smartphone addiction and psychological distress and internet gaming disorder is limited. This study investigated the characteristics and prevalence of smartphone addiction and its relation with psychological distress and internet gaming disorder. Furthermore, it provides the scientific basis for intervention measures in schools, families, and society.

A random cluster sampling method was applied to investigate 656 medical students from grades 1 to 4 at Wannan Medical College in Anhui province, People's Republic of China. The questionnaire consisted of general information, a smartphone addiction scale, an Internet gaming disorder scale, and a Kessler 6-item psychological distress test. The obtained results were first summarized using descriptive statistics. The Chi-square test was used to compare the status of smartphone addiction. Binary logistic regression was used to analyze the relationship between smartphone addiction and various variables.

Our results showed that the prevalence of smartphone addiction in medical students was 49.5% (325/656). Psychological distress (p < 0.001), internet gaming disorder (p < 0.001), and childhood trauma (p = 0.001) were highly correlated with smartphone addiction in medical students. Psychological distress, and internet gaming disorder were positively associated with smartphone addiction (p < 0.000).

The prevalence of smartphone addiction is high among medical students in Chinese. Smartphone addiction is highly related to related to internet gaming disorder and psychological distress.

The purpose of this investigation was to study the relationship between sleep quality, problematic smartphone use (PSU) and bedtime procrastination, as well as to assess gender and age differences. A total of 313 participants, aged 18-60 (M = 30 ± 10.1; 53.2% males), completed an online survey between February and May 2023 in Spain. The Pittsburgh Sleep Quality Index, Smartphone Addiction Scale-Short Version and Bedtime Procrastination Scale were used to measure sleep quality, PSU and bedtime procrastination, respectively. Additionally, smartphone use habits were evaluated through self-report questions. Pearson correlations, independent samples t-tests, one-way ANOVA, Bonferroni's post hoc tests and mediation analysis were conducted. Correlation analysis showed positive associations between the three main variables. Independent sample t-tests indicated females were more prone to PSU along with higher overall smartphone use. Post hoc analysis of one-way ANOVA exposed age differences between young adults (18-25 years old), adults (26-44 years old) and middle-aged adults (45-60 years old) in PSU and bedtime procrastination. Finally, mediation analysis revealed that PSU had indirect effects on sleep quality through bedtime procrastination, but no direct effects on sleep quality. Therefore, PSU, and especially bedtime procrastination, should be considered as targets in future campaigns or intervention programs to improve sleep quality among the young Spanish population.

Existing research has demonstrated that depression is positively related to smartphone addiction, but the role of sleep has not been discussed thoroughly, especially among engineering undergraduates affected by the coronavirus disease 2019 pandemic.

To evaluate sleep as a mediator of the association between smartphone addiction and depression among engineering undergraduates.

Using a multistage stratified random sampling method, a cross-sectional survey was conducted among 692 engineering undergraduates from a top engineering university in China, and data were collected by self-reported electronic questionnaires. The data included demographic characteristics, such as age, gender, the Smartphone Addiction Scale-Short Version (SAS-SV), the 9-item Patient Health Questionnaire, and the Pittsburgh Sleep Quality Index. Pearson correlation and multiple linear regression analyses were used to examine the association between smartphone addiction and depression, while structural equation models were established to evaluate the possible mediating role of sleep.

Based on the cutoffs of the SAS-SV, the rate of smartphone addiction was 63.58 percent, with 56.21 percent for women and 65.68 percent for men, among 692 engineering students. The prevalence of depression among students was 14.16 percent, with 17.65 percent for women, and 13.18 percent for men. Smartphone addiction was positively correlated with depression, and sleep played a significant mediating effect between the two, accounting for 42.22 percent of the total effect. In addition, sleep latency, sleep disturbances, and daytime dysfunction significantly mediated the relationship between depression and smartphone addiction. The mediating effect of sleep latency was 0.014 [P < 0.01; 95% confidence interval (CI): 0.006-0.027], the mediating effect of sleep disturbances was 0.022 (P < 0.01; 95%CI: 0.011-0.040), and the mediating effect of daytime dysfunction was 0.040 (P < 0.01; 95%CI: 0.024-0.059). The influence of sleep latency, sleep disturbances, and daytime dysfunction accounted for 18.42%, 28.95%, and 52.63% of the total mediating effect, respectively.

The results of the study suggest that reducing excessive smartphone use and improving sleep quality can help alleviate depression.

The use of smartphones among the general public and health care practitioners, in particular, is ubiquitous. The aim of this study was to investigate the relationship between smartphone addiction and sleep quality, psychological distress, and loneliness among health care students and workers in Saudi Arabia.

This cross-sectional study used an online questionnaire to collect data on smartphone addiction, sleep quality, psychological distress, and loneliness as well as demographic information.

A total of 773 health care students and workers participated in the study, with an average age of 25.95 ± 8.35, and 59.6% female participants. The study found a positive significant association between smartphone addiction and psychological distress (F(1,771) = 140.8, P < 0.001) and emotional loneliness (F(1,771) = 26.70, P < 0.001). Additionally, a significant negative association between smartphone addiction and sleep quality was found (F(1,771) = 4.208, P = 0.041). However, there was no significant relationship between smartphone addiction and social loneliness (F (1,771) = 0.544, P < 0.461).

These findings suggest that smartphone addiction has a negative impact on psychological distress, sleep quality, and emotional loneliness among health care students and workers. It is important to promote strategies to reduce smartphone dependency in order to avoid the harmful consequences of smartphone addiction.

Cell phones have increased dramatically as a new communication technology in the modern world. This study aimed to determine the relationship between cell phone over use scale with depression, anxiety and stress among university students in Khorramabad, Iran.

In this descriptive-analytical and cross-sectional study, 212 students were randomly selected from the Lorestan University of Medical Sciences by a combination of stratified and clustered random sampling. Data were collected by two standard questionnaires including, Cell-phone Over-use Scale (COS) and Depression, Anxiety and Stress (DASS-21) and were analyzed using SPSS V.22.

Based on the results, 72.2% of the students were exclusively male, which a majority of them were in age of 21-23 years (46.2%), and 92.5% were single. Based on the multiple linear regression and after adjustment for the confounding effect, there was a significant relationship between cell phone over use scale on student's stress (t = 2.614, P = 0.010), and student's anxiety (t = 2.209, P = 0.028); however there was not a significant relationship between cell phone over use scale on student's depression (t = 1.790, P = 0.075).

Harmful use of cell phones can aggravate psychological disorders such as anxiety, stress and depression and by controlling this factor can increase the level of mental health and improve the quality of life in students.

Lorestan University of Medical Sciences. ID: IR.LUMS.REC.1397-1-99-1253.

Although previous studies have shown that perceived stress is positively related to problematic smartphone use, knowledge of mediating and moderating mechanisms underpinning this relationship is quite limited. In this study, we explored whether experiential avoidance mediated the relationship between perceived stress and problematic smartphone use and whether trait mindfulness moderated this mediating process. A total of 763 Chinese college students completed the measures of perceived stress, experiential avoidance, problematic smartphone use, and trait mindfulness. The results indicate that perceived stress was positively related to problematic smartphone use and this relation was partially mediated by experiential avoidance. Furthermore, moderated mediation analysis showed that trait mindfulness moderated the linkage between perceived stress and problematic smartphone use via experiential avoidance. This link became weaker for college students with higher levels of trait mindfulness. The results highlight the value of identifying the underlying mechanisms between perceived stress and college students' problematic smartphone use.

Using a three-wave longitudinal design, we examined the relationship between early parent-child relationship and subsequent smartphone addiction (SA) and explored mediating and moderating mechanisms underlying this relation. A total of 527 Chinese adolescents (271 boys and 256 girls, mean age = 11.23 years) completed questionnaires regarding parent-child relationship, smartphone addiction, hope and life satisfaction. The results showed that: (1) parent-child relationship (T1) was positively associated with life satisfaction (T1) and hope (T2); parent-child relationship (T1), life satisfaction (T1), and hope (T2) were significantly negatively associated with SA (T3); (2) After controlling for age, gender, and SA (T1), hope (T2) completely mediated the relationship between parental-child relationship (T1) and adolescents' SA (T3); (3) life satisfaction (T1) moderated the association between parent-child relationship (T1) and hope (T2). Specifically, as life satisfaction (T1) increased, parent-child relationship (T1) was more likely to promote hope (T2). Moreover, the indirect negative links between parent-child relationship (T1) and SA (T3) via hope (T2) were stronger for adolescents with high level of life satisfaction (T1) than for adolescents with low level of life satisfaction (T1). The results reveal the mechanism of hope and life satisfaction in the effect of parent-child relationship on SA in adolescents, indicating that SA among adolescents can be weakened through the improvement of parent-child relationship, the rise in hope and the increase in life satisfaction.

To conduct a meta-analysis to quantitatively assess the association between mobile phone addiction (MPA) and sleep disorder (SD) by reviewing current evidence from observational studies.

The meta-analysis was conducted by searching Pubmed, Embase, Scopus, and Web of science using a retrieval strategy related to MPA and SD. Pooled Odds ratios and Pearson's correlation coefficients were calculated by R software using a random effects model.

29 studies including a total of 20041 participants were identified. We found that MPA was significantly associated with an increased risk of adolescents having SD (OR = 2.25, 95%CI= 1.72-2.94). Additionally, the findings also demonstrated that weak-to-moderate positive correlations were found between MPA and SD (summary r = 0.30, 95%CI= 0.25-0.34). The meta-regression analysis and subgroup analysis suggested that the geographic location and the measurement of MPA might be the sources of heterogeneity, and the robustness of the findings was confirmed by sensitivity analysis.

The information collected was self-reported, and the recall bias was inevitable.

This study updated the findings of the association between MPA and SD from the previous reviews and was also the first meta-analysis to assess the association between MPA and SD using Odds Radios and correlation coefficients concurrently. The result of this study re-emphasized that paying more attention to the public health concerns of MPA and SD is needed in the future, whether implementation more relevant researches or developing targeted policies.

Evidence supports predictive roles of non-social smartphone use for smartphone addiction, but the relationship of social smartphone use and smartphone addiction is unclear. This study explored whether social smartphone use has a double-edged impact on smartphone addiction. Using data from a sample of 909 Chinese undergraduates, we tested a parallel mediation model that considered online social support and realistic social support as mediators. As predicted, social smartphone use weakened smartphone addiction through realistic social support and contributed to smartphone addiction through online social support. Moreover, we tested the moderating role of agreeableness in the mediation path of online social support. Agreeableness only moderated the indirect effects. Specifically, the predictive effects of online social support on smartphone addiction was greater for lower rather than higher agreeableness. The results suggest that social needs play an important role in the formation of smartphone addiction. Several limitations and implications are also discussed herein.

Despite the high prevalence of both depression and smartphone addiction among Chinese adolescents, research examining their bidirectional relationship has been limited. Moreover, longitudinal research regarding the influence of maladaptive metacognitive beliefs on smartphone addiction is scarce. This 6-month longitudinal study aimed to address these research gaps by testing a cross-lagged panel model of maladaptive metacognition, depression, and smartphone addiction.

Four hundred and fifty-nine Chinese high school students voluntarily completed an anonymous questionnaire at baseline, and 313 of them (36.1% male; age = 14 to 18; M = 16.88, SD = 0.62) completed the same questionnaire at follow-up.

Positive correlations were shown among depression, smartphone addiction, and maladaptive metacognition at both waves (r = 0.16 to 0.57, p < .01). The results of the cross-lagged analysis demonstrated only the prospective effect of depression on smartphone addiction (β = 0.18, p < .001) but not vice versa. Moreover, maladaptive metacognition assessed at baseline significantly predicted subsequent depression (β = 0.14, p < .01) but not smartphone addiction (p>.05). Additional path analysis showed a significant indirect effect of baseline maladaptive metacognition (0.099 [95% CI = 0.042, 0.183]) on subsequent smartphone addiction, via depression.

Findings of this study showed that the relationship between depression and smartphone addiction was unidirectional rather than bidirectional among Chinese adolescents. Specifically, depression predicted smartphone addiction, while maladaptive metacognition predicted depression. Depression also mediated the relationship between maladaptive metacognition and smartphone addiction. The findings suggest that incorporating metacognition and depression interventions into smartphone addiction prevention designs for adolescents may be beneficial.

Background: Prior studies have indicated the complex relationships of smartphone use and smartphone addiction with mental health and life satisfaction. The purpose of this study was to investigate the structural relationships among smartphone use, smartphone addiction, mental health problems (e.g., depression, anxiety, stress [DAS] and satisfaction with life [SWL]). Methods: Cross-sectional data were collected by convenience sampling via an online survey of undergraduate students at a Midwestern university in the United States. The sample size of601 collected from undergraduate students that owned a smartphone and completed responses to the variables was utilized in this study. We assessed the hypothesized variables, including smartphone use, smartphone addiction, and mental health outcomes variables on a Likert-type scale. Structural analysis was used to examine the relationships. Results: Results suggested that smartphone use had a significant negative association with DAS symptoms (β = -.31, t = -3.81, P < .001) and was positively associated with SWL (β =.25, t = 3.41, P < .001). However, smartphone use had a significant positive relationship with smartphone addiction (β = .48, t = 5.51, P < .001). Smartphone addiction was positively related to DAS (β = .44, t = 6.33, P < .001), but it was not related to SWL (β = -.08, t = -1.26, P > .05). Conclusion: This study enhances our understanding of the associations between smartphone use and the health and well-being of undergraduate students. Implications for supporting their psychological health are discussed.

Background: As a device with multiple functions, a smartphone become more and more relevant in everyday life. However, this goes along with an increase in reports about smartphone addiction and its unwanted consequences. One of the most important variables in the etiopathogenesis of addictive smartphone use is personality. Objective: This study aimed to investigate predictors of problematic smartphone use. Clinically relevant differences in personality, psychopathology, and social support between students with and without problematic smartphone use were investigated. Method: All currently enrolled students at the Sigmund Freud University in Vienna (N = 1,836) were surveyed. Response rate was 27.07% (N = 497, age: M = 19.6, SD = 8.04). The Smartphone Addiction Scale (SPAS), the 10-Item Big Five Inventory (BFI-10), the Brief Symptom Inventory (BSI-18), and a questionnaire on social support (F-SozU-K-14) were used. Results: A total of 75 students (15.1% of the total sample) showed problematic smartphone use. In terms of personality, respondents with problematic smartphone use showed significantly higher values for extraversion and neuroticism compared than non-addicted users. Students with problematic smartphone use showed significantly higher levels in terms of depression and anxiety. Contrary to expectations, individuals with problematic smartphone use showed significantly higher values for perceived social support than with individuals without problematic smartphone use. Discussion: Therapy for problematic smartphone use should be carried out taking into account discussed, important etiological factors, such as personality.