scholarly journals Problematic Smartphone Use in a Large Nationally Representative Sample: Age, Reporting Biases, and Technology Concerns

2021 ◽  
Author(s):  
Sharon Horwood ◽  
Jeromy Anglim ◽  
Sumudu R. Mallawaarachchi
Keyword(s):  
Screen Time ◽  
Representative Sample ◽  
Female Age ◽  
Problematic Smartphone Use ◽  
Age Related ◽  
Generational Changes ◽  
Smartphone Use ◽  
Nationally Representative ◽  
Objectively Measured ◽  
Sample Age

This study utilized data from a nationally representative sample of Australian adults (n =1164; 50.7% female; age M = 44.9 years, SD = 16.3) to examine the relationships between age, technology concerns, self-rated and objective amount of smartphone use, and problematic smartphone use. Participants completed measures of problematic smartphone use and technology concern, while amount of smartphone use was self-rated and objectively measured using smartphone screen time reporting tools (Screen Time for iOS and Digital Wellbeing for Android). Amount of self-rated and objective smartphone use declined linearly with age. In contrast, problematic smartphone use was relatively high and stable in young adults before rapidly declining around age 40. People were reasonably good at estimating their amount of smartphone use (r = .73), although they did tend to underestimate usage. Technology concern was high across all ages, but unrelated to amount of usage and problematic smartphone usage. Age related differences are interpreted in terms of a combination of developmental and generational changes. Results also suggest that amount of use is an important but not complete cause of problematic smartphone use.

scholarly journals Smartphone use motivation and problematic smartphone use in a national representative sample of Chinese adolescents: The mediating roles of smartphone use time for various activities

2020 ◽  
Vol 9 (1) ◽  
pp. 163-174 ◽  
Author(s):  
Haoran Meng ◽  
Hongjian Cao ◽  
Ruining Hao ◽  
Nan Zhou ◽  
Yue Liang ◽  
...  
Keyword(s):  
Emerging Adults ◽  
Representative Sample ◽  
Cultural Context ◽  
Life Stage ◽  
Chinese Adolescents ◽  
Survey Study ◽  
Problematic Smartphone Use ◽  
Smartphone Use ◽  
Using Data ◽  
National Representative Sample

Abstract Background and aims Previous studies on smartphone use motivation (SUM) and problematic smartphone use (PSU) have been limited in the utilization of regional samples of emerging adults (e.g., college students) and also in the foci on the direct association between SUM and PSU. To address such gaps, using data from a large, national representative sample of Chinese young adolescents and their parents this study examined the associations between adolescents' various types of SUM and their PSU, and also tested the potential mediating roles of smartphone use time (SUT) that adolescents spent on various activities in such associations. Methods A nationwide representative sample of 8,261 Chinese adolescents (Mage = 12.86 years old, SD = 1.76; 42.6% females) and their parents (49% mothers) participated in this survey study. Results Instrumental SUM (i.e., to expand knowledge or acquire information) was associated negatively with PSU via longer SUT spent on learning and shorter SUT spent on entertainment and communication. Self-expression SUM (i.e., to gain acceptance and recognition of others by maintaining or improving self-images) was associated with longer SUT spent on both learning and entertainment, which, in turn, predicted lower and higher levels of PSU, respectively. Last, hedonic SUM (i.e., to gain pleasure) was associated positively with PSU via longer SUT spent on entertainment and communication. Discussion These findings contribute to the literature by adding greater specificity in our understanding of the implications of SUM and SUT in the etiology of PSU during the critical life stage of adolescence in a Chinese cultural context.

scholarly journals A ten-step behavioural intervention to reduce screen time and problematic smartphone use

2021 ◽  
Author(s):  
Jay A. Olson ◽  
Dasha Sandra ◽  
Denis Chmoulevitch ◽  
Amir Raz ◽  
Samuel P. L. Veissière
Keyword(s):  
Depressive Symptoms ◽  
Technology Use ◽  
Screen Time ◽  
Intervention Study ◽  
Well Being ◽  
Control Group ◽  
Behavioural Intervention ◽  
Problematic Smartphone Use ◽  
The World ◽  
Smartphone Use

Problematic smartphone use is rising across the world and has been associated with reductions in concentration and well-being. Few interventions aiming to reduce smartphone use take a multi-faceted approach that balances feasibility and effectiveness. We developed such an intervention with ten simple guidelines that nudge users to reduce their screen time (e.g., disabling non-essential notifications). Two pre-registered studies tested the intervention. Study 1 (N = 51) found reductions in screen time, problematic smartphone use, and depressive symptoms after two weeks. Study 2 (N = 70) found that the intervention caused larger changes in screen time, problematic smartphone use, and sleep quality than a control group of screen time monitoring alone. Our brief intervention reduced screen time by one hour per day and returned problematic smartphone use scores to normal levels for at least six weeks. This intervention provides simple, scalable, and feasible behavioural guidelines to promote healthy technology use.

Instagram use frequency is associated with problematic smartphone use, but not with depression and anxiety symptom severity

2020 ◽  
Vol 8 (3) ◽  
pp. 400-418 ◽  
Author(s):  
Dmitri Rozgonjuk ◽  
Patrik Pruunsild ◽  
Kadi Jürimäe ◽  
Rosiine-Johanna Schwarz ◽  
Jaan Aru
Keyword(s):  
Indirect Effects ◽  
Online Survey ◽  
Anxiety Symptom ◽  
Demographic Variables ◽  
Bivariate Analysis ◽  
Depression And Anxiety ◽  
Problematic Smartphone Use ◽  
Younger Age ◽  
Smartphone Use ◽  
Objectively Measured

Studies have demonstrated that social media use, as well as problematic smartphone use (PSU), are associated with psychopathology variables, such as depression and anxiety. However, it has not been studied how Instagram use frequency is associated with depression, anxiety, and PSU. The aim of this study was to investigate whether Instagram use frequency is related to these psychopathology variables. Three hundred and five active Instagram users ( Mage = 23.61, SDage = 5.33; 82.2% female) comprised the effective sample in this study. They responded to an online survey that included questionnaires regarding their Instagram and smartphone use, as well as about experiencing depression and anxiety symptoms. We also retrieved objectively measured Instagram use data. The results showed that although Instagram use frequency, depression, and anxiety were associated with PSU in bivariate analysis, Instagram use frequency did not have indirect effects in the relations between psychopathology variables and PSU. Furthermore, while younger age and female sex predicted Instagram use frequency, these socio-demographic variables did not predict PSU. According to our findings Instagram use frequency contributes to PSU, but it is not related to depression and anxiety.

Demographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study

2019 ◽  
Vol 50 (9) ◽  
pp. 1539-1547 ◽  
Author(s):  
Joshua C. Gray ◽  
Natasha A. Schvey ◽  
Marian Tanofsky-Kraff
Keyword(s):  
Screen Time ◽  
Representative Sample ◽  
Social Problems ◽  
Inductive Reasoning ◽  
Attention Problems ◽  
Cognitive Variables ◽  
Stimulant Use ◽  
Cognitive Correlates ◽  
Nationally Representative ◽  
Matrix Reasoning

AbstractBackgroundPrevious research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth.MethodsMultiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g. demographics) and potentially modifiable (e.g. psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9–10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.ResultsThe full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e. nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex.ConclusionsBeyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.

scholarly journals Smartphone addiction is increasing across the world: A meta-analysis of 24 countries

2020 ◽  
Author(s):  
Jay A. Olson ◽  
Dasha Sandra ◽  
Élissa S. Colucci ◽  
Alain Al Bikaii ◽  
Johnny Nahas ◽  
...  
Keyword(s):  
Screen Time ◽  
Meta Analysis ◽  
Global Scale ◽  
Smartphone Addiction ◽  
Problematic Smartphone Use ◽  
Targeted Interventions ◽  
The World ◽  
Teenagers And Young Adults ◽  
Smartphone Use ◽  
Global Norms

Smartphone ownership and screen time are increasing across the world, but there have been few attempts to quantify smartphone addiction on a global scale. We conducted a meta-analysis of studies published between 2014 and 2020 that used the Smartphone Addiction Scale, the most common measure of problematic smartphone use. This scale measures whether smartphone use interferes with one’s daily life. We focused on studies of teenagers and young adults (aged 15 to 35) since they show the highest screen time and smartphone ownership rates. Across 85 samples, 24 countries, and 39,292 participants, we demonstrate that problematic smartphone use is increasing across the world. China, Saudi Arabia, and Malaysia had the highest scores while Switzerland, Germany, and France had the lowest. Our results provide global norms for researchers and can help identify countries that could benefit from targeted interventions.

Demographic, Psychological, Behavioral, and Cognitive Correlates of BMI in Youth: Findings from the Adolescent Brain Cognitive Development Study

2019 ◽  
Author(s):  
Joshua Gray ◽  
Natasha Schvey ◽  
Marian Tanofsky-Kraff
Keyword(s):  
Screen Time ◽  
Representative Sample ◽  
Social Problems ◽  
Inductive Reasoning ◽  
Attention Problems ◽  
Cognitive Variables ◽  
Stimulant Use ◽  
Cognitive Correlates ◽  
Nationally Representative ◽  
Matrix Reasoning

Background: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth. Methods: Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g., demographics) and potentially modifiable (e.g., psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9-10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.Results: The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e., nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex. Conclusions: Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.

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