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Cell-Phone Addiction: A Review

Affiliations.

1 Department of Psychobiology, Psychology Faculty, Complutense University of Madrid (Universidad Complutense de Madrid) , Madrid , Spain.
2 Department of Psychobiology, Psychology Faculty, Complutense University of Madrid (Universidad Complutense de Madrid), Madrid, Spain; Clinical Management of Mental Health Unit, Biomedical Research Institute of Málaga, Regional University Hospital of Málaga (Unidad de Gestión Clínica de Salud Mental, Hospital Regional Universitario de Málaga, Instituto de Investigación Biomédica de Málaga - IBIMA), Málaga, Spain.
3 Istituto de Investigación i+12, Hospital Universitario 12 de Octubre de Madrid , Madrid , Spain.
PMID: 27822187
PMCID: PMC5076301
DOI: 10.3389/fpsyt.2016.00175

We present a review of the studies that have been published about addiction to cell phones. We analyze the concept of cell-phone addiction as well as its prevalence, study methodologies, psychological features, and associated psychiatric comorbidities. Research in this field has generally evolved from a global view of the cell phone as a device to its analysis via applications and contents. The diversity of criteria and methodological approaches that have been used is notable, as is a certain lack of conceptual delimitation that has resulted in a broad spread of prevalent data. There is a consensus about the existence of cell-phone addiction, but the delimitation and criteria used by various researchers vary. Cell-phone addiction shows a distinct user profile that differentiates it from Internet addiction. Without evidence pointing to the influence of cultural level and socioeconomic status, the pattern of abuse is greatest among young people, primarily females. Intercultural and geographical differences have not been sufficiently studied. The problematic use of cell phones has been associated with personality variables, such as extraversion, neuroticism, self-esteem, impulsivity, self-identity, and self-image. Similarly, sleep disturbance, anxiety, stress, and, to a lesser extent, depression, which are also associated with Internet abuse, have been associated with problematic cell-phone use. In addition, the present review reveals the coexistence relationship between problematic cell-phone use and substance use such as tobacco and alcohol.

Keywords: addiction; behavioral addiction; cell-phone addiction; dependence; internet addiction.

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MINI REVIEW article

Excessive smartphone use is associated with health problems in adolescents and young adults.

$\nYehuda Wacks$

Department of Behavioral Sciences, Ariel University, Ariel, Israel

Background and Aims: This present paper will review the existing evidence on the effects of excessive smartphone use on physical and mental health.

Results: Comorbidity with depression, anxiety, OCD, ADHD and alcohol use disorder. Excessive smartphone use is associated with difficulties in cognitive-emotion regulation, impulsivity, impaired cognitive function, addiction to social networking, shyness and low self-esteem. Medical problems include sleep problems, reduced physical fitness, unhealthy eating habits, pain and migraines, reduced cognitive control and changes in the brain's gray matter volume.

In Conclusion: Excessive smartphone use is associated with psychiatric, cognitive, emotional, medical and brain changes that should be considered by health and education professionals.

Introduction

Excessive smartphone use in young adults.

The effects of excessive use of computer screens and smartphones are raising serious concerns among health and educational authorities due to negative effects of such use in children and adolescents. Recent reviews have argued that the evidence supporting excessive smartphone use as an addictive behavior is scarce. In particular, Billieux ( 1 ) have argued that there is insufficient evidence for behavioral and neurobiological similarities between excessive smartphone use other types of addictive behaviors. Panova and Carbonell ( 2 ) also argued that there is insufficient evidence to support for the diagnosis of smartphone addiction and finally Montag et al. ( 3 ) have argued that excessive smartphone use is a form of Internet Use Disorder. The smartphones are being used for various purposes such as gaming, Social Network Services (SNS), watching video clips (YouTube). Therefore, excessive use of smartphones may have difference characteristics according to the type of smartphone use. This present paper will review the existing evidence on excessive smartphone use, and it will discuss its similarities with and differences from Internet addiction.

A PubMed Central ® and Web of Science search engines have been used with the terms: “excessive smartphone use” and “smartphone addiction” until February 2021 that resulted in 84 research studies in English language.

Predictors of Excessive Smartphone-Use

The main factors predicting excessive smartphone use were being female, preoccupation, conflict, and use for ubiquitous trait whereas the protective factor was use for learning ( 4 ). Excessive use of smartphones was correlated with impairment in the function of the family and relationship with friends, impulsiveness, and low self-esteem in South Korean adolescents ( 5 ). Finally, smartphone gaming was associated with excessive smartphone use among adolescents ( 6 ).

Sensation Seeking and Boredom

Turgeman et al. ( 7 ) have reported an interaction between high sensation seeking and abstinence whereby abstinence for 1.5 h increased excessive smartphone use ratings in high sensation seeking students. This may be explained by boredom, avoidance of uncomfortable situations and the need for entertainment ( 8 – 12 ). Lepp et al. ( 13 ) have found an association between excessive smartphone use and living sedentary life or being an “active couch potato. “Ben-Yehuda et al. ( 14 ) have investigated the effects of involvement and of interest in three conditions: state of boredom, passive activity and active activity in counter-balanced order in University students. Excessive smartphone use was not influenced by any interest or involvement in the lecture, indicating a compulsive behavior. Finally, Li et al. ( 15 ) have demonstrated that individuals with an external locus of control had less control over their smartphone use and therefore could have more negative effects such as poor sleep quality, lower academic achievements, and lower ratings of well-being.

Insecure Attachment, Poor Cognitive-Emotional Regulation and Communication Problems

Insecure attachment positively correlated with problematic smartphone use in students with unhealthy family function but not with mother-infant bonding or maternal mental health ( 16 ). Eichenberg et al. ( 17 ) showed an association between excessive smartphone use and an insecure attachment style in Problematic adolescent users. A following study reported high scores in maladaptive Cognitive-emotion regulation (CER) strategies such as self-blame, blaming of others ruminating and catastrophizing thoughts ( 18 ). Experiential avoidance (i.e., attempts to avoid thoughts, feelings, memories and physical sensations) has been associated with excessive smartphone use and social networks ( 19 ). Childhood emotional maltreatment correlated with problematic smartphone use in adolescents, and it was mediated by body image difficulties, depression, and social anxiety ( 20 ). Emotion regulation difficulties, unregulated eating, restrained eating, food addiction, and higher percent body fat were associated with excessive smartphone use among adolescents ( 21 ). Mahapatra ( 22 ) showed a strong association between both lack of self-regulation and loneliness on problematic smartphone use among adolescents that ultimately resulted in family, interpersonal conflicts, and poor academic performance. Among students, problematic smartphone users have shown high measures of worry and anger ( 23 ) whereas excessive reassurance seeking behavior mediated the association between rumination and problematic smartphone use ( 24 ). Poor communication skills were shown in Medical students who preferred to communicate emotions through texting rather than verbal communication ( 25 ) and they correlated with excessive smartphone use ( 26 ). Excessive use of the smartphone has negative impacts on people's lives by reducing face-to-face interactions, and increasing loneliness ( 27 ).

Impaired Cognitive Function

Problems in inhibitory control mechanisms in excessive smartphone users were reported ( 28 ). They have reported that while performing on the Go/NoGo task excessive smartphone users showed a negative N2 event-related potentials (ERPs) component showing reduced inhibitory control. There is further evidence for impaired attention, reduced numerical processing capacity, increased impulsivity, hyperactivity and negative social concern in heavy smartphone users ( 29 ). Heavy smartphone users showed. Inattention problems correlated with Transcranial Magnetic Stimulation (TMS) evoked potentials in the right prefrontal cortex. Wegmann et al. ( 30 ) have found no correlations between problematic social networks use and executive function and inhibitory control measured by the Go/NoGo task. However, regression analyses showed that increased problematic social networks use is associated with higher impulsivity, especially if executive functions or specific inhibitory control were impaired.

Social Media Use and Personality

Problematic social media use has been shown to be associated with “fear of missing out” (FOMO) ( 31 , 32 ). FOMO mediated relations between both fear of negative and positive evaluation with both problematic and social smartphone use. Withdrawal and FOMO ratings were higher among participants with 72 h restricted access to smartphones compared with those without ( 33 ). There was a correlation between Social communication use and excessive use of smartphones. FOMO mediated the relationships between anxiety and depression with problematic smartphone use ( 24 , 34 ). Excessive smartphone use has been associated with social comparisons on social networking sites and perceived stress ( 35 ). Personality factors such as conscientiousness, openness, emotional stability and neuroticism have been associated with problematic smartphone use ( 36 , 37 ) whereas impulsivity, excessive reassurance seeking, but not extraversion related to problematic smartphone use in other studies ( 38 , 39 ).

Comorbidity With Anxiety, Depression OCD, ADHD and Alcohol Use Disorder

There are several studies on the comorbidity of excessive smartphone use and mental disorders and its association with sleep problems, reduced fitness and pain. Excessive smartphone use has been associated with depression, anxiety ( 40 , 41 ) and social anxiety ( 7 , 42 – 44 ) shyness and low self-esteem ( 5 – 12 , 12 – 47 ) low psychological well-being ( 48 ) and low mental well-being ( 49 ). Excessive reassurance seeking correlated with problematic smartphone use severity, and its combination with rumination mediated the relationship between depression and anxiety severity with problematic smartphone use ( 50 ). Anxiety during the COVID-19 epidemic correlated with severity of problematic smartphone use, depression and generalized anxiety ( 51 ).

Early problematic smartphone use was found as a significant predictor of depression in a three-year longitudinal study from adolescence to emerging adulthood ( 52 ). Excessive mobile use was associated with high levels of depressive moods, with loneliness serving as a moderator of this mediation particularly in men ( 53 ). Depression and anxiety were significantly associated with both excessive smartphone use ( 54 ). Depressive mood and suicidal ideation were associated with social network smartphone use ( 55 ). Interestingly, the time spent in excessive smartphone use has predicted the level of stress in users who hardly used the smartphone for self-disclosure whereas those who engaged in disclosure of their emotions and problems online, this reduced their emotional problems ( 56 ). Problematic smartphone use has been associated with psychological distress and emotion dysregulation and emotion dysregulation was shown as a mediator in the relation between psychological distress and problematic smartphone use ( 57 ). Excessive smartphone use has been also associated with Obsessive Compulsive Disorder symptoms ( 58 ) and ADHD ( 59 , 60 ).

History of alcoholism and father's education level explained 26% of the variance of problematic smartphone use ( 60 ). In addition, alcohol use disorder, impulsivity (Barratt scale and ADHD) and elevated occurrence of PTSD, anxiety, and depression were associated with excessive smartphone use ( 61 ). Finally, the relationship between PTSD severity and problematic smartphone use was mediated by negative urgency (a component of impulsivity) ( 62 ).

Medical Complications- Sleep, Physical Fitness, Eyesight, Migraine and Pain

Excessive smartphone use was associated with reduced sleep time and sleep quality in adolescents ( 63 ). The association between media use in bed before sleep and depression was mediated by sleep disturbance ( 64 , 65 ). Furthermore, there was an association between excessive screen time and problems in sleep onset ( 66 ), insufficient sleep ( 67 ), and insomnia ( 68 ). Long-term problematic mobile use predicted new incidences of sleep disturbances and mental distress, which was ameliorated by its discontinuation ( 69 ). Excessive mobile phone use correlated with disturbed sleep pattern and quality ( 70 ) Excessive smartphone use was associated with poorer sleep quality and higher perceived stress ( 71 , 72 ), lowered physical activity, lower muscle mass and higher fat mass ( 73 ). Other medical conditions include acquired comitant esotropia (AACE) ( 74 ) increased ocular symptoms ( 75 ), headache complaints ( 76 , 77 ) and headache duration and frequency in migraine patients ( 78 ). Young chronic neck pain patients with overuse of smartphones had higher Cervical Disc Degeneration ( 79 ). Finally, excessive smartphone users had higher median nerve Cross sectional areas (CSA's) in their dominant hands ( 80 ).

Brain Imaging

A recent study has used diffusion MRI for assessment of white matter structural connectivity, and it has shown a positive association between activity in the right amygdala and excessive smartphone use in adolescents ( 81 ). Excessive smartphone users have shown impairment in cognitive control during emotional processing of angry faces and social interaction in fMRI ( 82 ). They also showed reduced functional connectivity in regions related to cognitive control of emotional stimuli including reward ( 83 ). Reduced Gray Matter Volume (GMV) was shown in problematic smartphone users and negative correlations between GMV in the right lateral Orbito Frontal Cortex (OFC) and measures of smartphone addiction ( 84 ). Lower activity in the right anterior cingulate cortex (ACC) and a negative correlation between individuals with excessive smartphone use and both ACC GMV and activity was reported ( 85 ). Furthermore, the strength of the resting state functional connectivity (rsFC) between several brain regions in fMRI positively correlated with smartphone time in bed ( 86 ). Finally, exposure to smartphone pictures in fMRI was associated with activation of brain regions associated with drug addiction and correlations of these regions with smartphone addiction scores were reported ( 87 ).

Supplementary Table 1 shows details of the studies reviewed in this paper.

There have been several reviews in recent years that have discussed the issue whether excessive smartphone use is considered a behavioral addiction ( 1 , 2 ). In addition, studies have examined whether there are differences between excessive smartphone use and Internet use disorder (IUD). Montag et al. ( 3 ) have proposed that excessive smartphone use is essentially a type of IUD. In this sense, IUD should be divided into two types of use: a mobile use and a non-mobile use. They have suggested that there is a specific use of IUD of a particular content and a generalized IUD where several channels are overused. The rationale for this division is that motivation, cognitive and affective factors predispose individuals to prefer a specific application and type of device.

However, there is little empirical evidence in support of these assumptions ( 88 , 89 ). Although there may be small differences between some mechanisms and risk factors underlying online behavioral addictions, such as pornography use, gaming disorder and social network use, the resemblance between them is very strong ( 90 ). In addition, there are few studies that have examined whether specific cognitive and motivational mechanisms could lead to a preference of a specific type of device. Nevertheless, recent studies show that excessive use of the screens including, computer screens and smartphones is associated with serious mental problems and cognitive impairments ( 91 , 92 ). Therefore, we argue that research should focus on the negative consequences of excessive smartphone use rather than on whether it should be considered as a behavioral addiction.

Recent studies show that excessive smartphone use is associated with problems of mental health and impaired psychological well-being. There is consistent evidence for comorbidity between excessive smartphone use and other psychiatric disorders, such as depression, anxiety, OCD, and ADHD similar to Internet addiction ( 93 ). In addition, excessive smartphone use is related to loneliness, stress, and other negative emotions ( 56 , 94 ).

In addition to these psychological consequences, the excessive use of smartphones can potentially lead to impairments of cognitive functions. Such excessive use is related to impairments of specific attention domains (such as focused attention and divided attention), low inhibitory control, impaired working memory, reduced numerical processing capacity, and changes in social cognition. Since cognition and emotion are often intertwined it is not surprising that a common cognitive-emotional mechanism related to loss of control would be associated with impulsiveness, impairment in communication and relationship with friends and family.

Recent studies have also shown an association between an excessive use of smartphones and abnormal activity of regions in the prefrontal cortex and in the networks that connect to these regions ( 29 , 82 ). Novel findings show reduced lateral orbitofrontal gray matter, especially in social networking platforms overuse and that prolonged bedtime smartphone use has been associated with altered insula-centered functional connectivity. Gray matter volume reduction was observed also in the anterior cingulate similar to Internet and gaming disorder ( 95 ). Excessive smartphone use has also been associated with reduced cognitive control during the emotional processing in the brain.

The effects of excessive use of the media including TV, computer screens and smartphones is raising serious concerns among health and educational authorities due to deleterious effects of such use in children and adolescents. A recent study has shown an association between increased screen-based media use and lower microstructural integrity of brain white matter tracts that are associated with language and literacy skills in 5-year-old pre- school children, ( 96 ). Furthermore, a large study of 4,277 adolescents has shown a negative correlation between screen media activity and cortical thickness in fMRI implying premature aging of the brain ( 97 ). Finally, young adults and heavy media “multi-taskers” are more susceptible to interference from irrelevant environmental stimuli and from irrelevant representations in memory, and they performed worse on a task-switching ability ( 98 ). The findings so far that span from early childhood to adolescents, rapidly growing societal phenomena, emphasize the need to assess the effects of media screens on cognitive function and the brain in children, adolescents and young adults.

Excessive smartphone use shares underlying mechanisms with other addictive behaviors such as gambling disorder, in particular, reduced cognitive control and impaired activity in the prefrontal cortex which affects decision-making and emotional processing ( 99 ). Addictions in adolescents share the tendency to experience poor emotional regulation, impulsivity and impaired cognitive control and reduced ability to experience pleasure in everyday life ( 100 ).

The major limitations in studies of excessive smartphone use and Internet addiction are that they are mainly cross-sectional studies without baseline measures and rely on associations between structural and functional changes in the brain and subjective measures and no proof of a causal role in the development of the adolescent or adult brain. Finally, the review is non-systematic and it has excluded non-English language articles.

The excessive use of the smartphone has been associated with impaired cognitive functions and mental health problems. There are unique findings on the association between using smartphones, need of constant stimulation, deficits in everyday cognitive functioning and brain changes which should send alarm signals to clinicians and educators in the modern world.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2021.669042/full#supplementary-material

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Keywords: internet addiction, smartphone addiction, problematic smartphone use, internet use disorder, excessive smartphone use

Citation: Wacks Y and Weinstein AM (2021) Excessive Smartphone Use Is Associated With Health Problems in Adolescents and Young Adults. Front. Psychiatry 12:669042. doi: 10.3389/fpsyt.2021.669042

Received: 17 February 2021; Accepted: 26 April 2021; Published: 28 May 2021.

Reviewed by:

Copyright © 2021 Wacks and Weinstein. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Aviv M. Weinstein, avivweinstein@yahoo.com ; avivwe@ariel.ac.il

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Open Access

Peer-reviewed

Research Article

Mobile phones: The effect of its presence on learning and memory

Roles Conceptualization, Data curation, Investigation, Writing – original draft

Affiliation Department of Psychology, Sunway University, Selangor, Malaysia

Roles Formal analysis, Investigation, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Clarissa Theodora Tanil,
Min Hooi Yong

Published: August 13, 2020
https://doi.org/10.1371/journal.pone.0219233
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Our aim was to examine the effect of a smartphone’s presence on learning and memory among undergraduates. A total of 119 undergraduates completed a memory task and the Smartphone Addiction Scale (SAS). As predicted, those without smartphones had higher recall accuracy compared to those with smartphones. Results showed a significant negative relationship between phone conscious thought, “how often did you think about your phone”, and memory recall but not for SAS and memory recall. Phone conscious thought significantly predicted memory accuracy. We found that the presence of a smartphone and high phone conscious thought affects one’s memory learning and recall, indicating the negative effect of a smartphone proximity to our learning and memory.

Citation: Tanil CT, Yong MH (2020) Mobile phones: The effect of its presence on learning and memory. PLoS ONE 15(8): e0219233. https://doi.org/10.1371/journal.pone.0219233

Editor: Barbara Dritschel, University of St Andrews, UNITED KINGDOM

Received: June 17, 2019; Accepted: July 30, 2020; Published: August 13, 2020

Copyright: © 2020 Tanil, Yong. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript.

Funding: MHY received funding from Sunway University (GRTIN-RRO-104-2020 and INT-RRO-2018-49).

Competing interests: The authors have declared that no competing interests exist.

Introduction

Smartphones are a popular communication form worldwide in this century and likely to remain as such, especially among adolescents [ 1 ]. The phone has evolved from basic communicative functions–calls only–to being a computer-replacement device, used for web browsing, games, instant communication on social media platforms, and work-related productivity tools, e.g. word processing. Smartphones undoubtedly keep us connected; however, many individuals are now obsessed with them [ 2 , 3 ]. This obsession can lead to detrimental cognitive functions and mood/affective states, but these effects are still highly debated among researchers.

Altmann, Trafton, and Hambrick suggested that as little as a 3-second distraction (e.g. reaching for a cell phone) is adequate to disrupt attention while performing a cognitive task [ 4 ]. This distraction is disadvantageous to subsequent cognitive tasks, creating more errors as the distraction period increases, and this is particularly evident in classroom settings. While teachers and parents are for [ 5 ] or against cell phones in classrooms [ 6 ], empirical evidence showed that students who used their phones in class took fewer notes [ 7 ] and had poorer overall academic performance, compared to those who did not [ 8 , 9 ]. Students often multitask in classrooms and even more so with smartphones in hand. One study showed no significant difference in in-class test scores, regardless of whether they were using instant messaging [ 10 ]. However, texters took a significantly longer time to complete the in-class test, suggesting that texters required more cognitive effort in memory recall [ 10 ]. Other researchers have posited that simply the presence of a cell phone may have detrimental effects on learning and memory as well. Research has shown that a mobile phone left next to the participant while completing a task, is a powerful distractor even when not in use [ 11 , 12 ]. Their findings showed that mobile phone participants could perform similarly to control groups on simple versions of specific tasks (e.g. visual spatial search, digit cancellation), but performed much poorer in the demanding versions. In another study, researchers controlled for the location of the smartphone by taking the smartphones away from participants (low salience, LS), left the smartphone next to them (high salience/HS), or kept the smartphones in bags or pockets (control) [ 13 ]. Results showed that participants in LS condition performed significantly better compared to HS, while no difference was established between control and HS conditions. Taken together, these findings confirmed that the smartphone is a distractor even when not in use. Further, smartphone presence also increases cognitive load, because greater cognitive effort is required to inhibit distractions.

Reliance on smartphones has been linked to a form of psychological dependency, and this reliance has detrimental effect on our affective ‘mood’ states. For example, feelings of anxiety when one is separated from their smartphones can interfere with the ability to attend to information. Cheever et al. observed that heavy and moderate mobile phone users reported increased anxiety when their mobile phone was taken away as early as 10 minutes into the experiment [ 14 ]. They noted that high mobile phone usage was associated with higher risk of experiencing ‘nomophobia’ (no mobile phone phobia), a form of anxiety characterized by constantly thinking about one’s own mobile phones and the desire to stay in contact with the device [ 15 ]. Other studies reported similar separation-anxiety and other unpleasant thoughts in participants when their smartphones were taken away [ 16 ] or the usage was prohibited [ 17 , 18 ]. Participants also reported having frequent thoughts about their smartphones, despite their device being out of sight briefly (kept in bags or pockets), to the point of disrupting their task performance [ 13 ]. Taken together, these findings suggest that strong attachment towards a smartphone has immediate and lasting negative effects on mood and appears to induce anxiety.

Further, we need to consider the relationship between cognition and emotion to understand how frequent mobile phone use affects memory e.g. memory consolidation. Some empirical findings have shown that anxious individuals have attentional biases toward threats and that these biases affect memory consolidation [ 19 , 20 ]. Further, emotion-cognition interaction affects efficiency of specific cognitive functions, and that one’s affective state may enhance or hinder these functions rapidly, flexibly, and reversibly [ 21 ]. Studies have shown that positive affect improves visuospatial attention [ 22 ], sustained attention [ 23 ], and working memory [ 24 ]. The researchers attributed positive affect in participants’ improved controlled cognitive processing and less inhibitory control. On the other hand, participants’ negative affect had fewer spatial working memory errors [ 23 ] and higher cognitive failures [ 25 ]. Yet, in all of these studies–the direction of modulation, intensity, valence of experiencing a specific affective state ranged widely and primarily driven by external stimuli (i.e. participants affective states were induced from watching videos), which may not have the same motivational effect generated internally.

Present study

Prior studies have demonstrated the detrimental effects of one’s smartphone on cognitive function (e.g. working memory [ 13 ], visual spatial search [ 12 ], attention [ 11 ]), and decreased cognitive ability with increasing attachment to one’s phone [ 14 , 16 , 26 ]. Further, past studies have demonstrated the effect of affective state on cognitive performance [ 19 , 20 , 22 – 25 , 27 ]. To our knowledge, no study has investigated the effect of positive or negative affective states resulting from smartphone separation on memory recall accuracy. One study showed that participants reporting an increased level of anxiety as early as 10 minutes [ 14 ]. We also do not know the extent of smartphone addiction and phone conscious thought effects on memory recall accuracy. One in every four young adults is reported to have problematic smartphone use and this is accompanied by poor mental health e.g. higher anxiety, stress, depression [ 28 ]. One report showed that young adults reached for their phones 86 times in a day on average compared to 47 times in other age groups [ 29 ]. Young adults also reported that they “definitely” or “probably” used their phone too much, suggesting that they recognised their problematic smartphone use.

We had two main aims in this study. First, we replicated [ 13 ] to determine whether ‘phone absent’ (LS) participants had higher memory accuracy compared to the ‘phone present’ (HS). Second, we predicted that participants with higher smartphone addiction scores (SAS) and higher phone conscious thought were more likely to have lower memory accuracy. With regards to separation from their smartphone, we hypothesised that LS participants will experience an increase of negative affect or a decrease in positive affect and that this will affect memory recall negatively. We will also examine whether these predictor variables–smartphone addiction, phone conscious thought and affect differences—predict memory accuracy.

Materials and methods

Participants.

A total of 119 undergraduate students (61 females, M age = 20.67 years, SD age = 2.44) were recruited from a private university in an Asian capital city. To qualify for this study, the participant must own a smartphone and does not have any visual or auditory deficiencies. Using G*Power v. 3.1.9.2 [ 30 ], we require at least 76 participants with an effect size of d = .65, α = .05 and power of (1-β) = .8 based on Thornton et al.’s [ 11 ] study, or 128 participants from Ward’s study [ 13 ].

Out of 119 participants, 43.7% reported using their smartphone mostly for social networking, followed by communication (31.1%) and entertainment (17.6%) (see Table 1 for full details on smartphone usage). Participants reported an average smartphone use of 8.16 hours in a day ( SD = 4.05). There was no significant difference between daily smartphone use for participants in the high salience (HS) and low salience groups (LS), t (117) = 1.42, p = .16, Cohen’s d = .26. Female participants spent more time using their smartphones over a 24-hour period ( M = 9.02, SD = 4.10) compared to males, ( M = 7.26, SD = 3.82), t (117) = 2.42, p = .02, Cohen’s d = .44.

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https://doi.org/10.1371/journal.pone.0219233.t001

Ethical approval and informed consent

The study was conducted in accordance with the protocol approved by the Department of Psychology Research Ethics Committee at Sunway University (approval code: 20171090). All participants provided written consent before commencing the study and were not compensated for their participation in the study.

Study design

Our experimental study was a mixed design, with smartphone presence (present vs absent) as a between-subjects factor, and memory task as a within-subjects factor. Participants who had their smartphone out of sight formed the ‘Absent’ or low-phone salience (LS) condition, and the other group had their smartphone placed next to them throughout the study, ‘Present’ or high-phone salience (HS) condition. The dependent variable was recall accuracy from the memory test.

Working memory span test.

A computerized memory span task ‘Operation Span (OS)’ retrieved from software Wadsworth CogLab 2.0 was used to assess working memory [ 31 ]. A working memory span test was chosen as a measure to test participants’ memory ability for two reasons. First, participants were required to learn and memorize three types of stimuli thus making this task complex. Second, the duration of task completion took approximately 20 minutes. This was advantageous because we wanted to increase separation-anxiety [ 16 ] as well as having the most pronounced effect on learning and memory without the presence of their smartphone [ 9 ].

The test comprised of three stimulus types, namely words (long words such as computer, refrigerator and short words like pen, cup), letters (similar sound E, P, B, and non-similar sound D, H, L) and digits (1 to 9). The test began by showing a sequence of items on the left side of the screen, with each item presented for one second. After that, participants were required to recall the stimulus from a 9-button box located on the right side of the screen. In order to respond correctly, participants were required to click on the buttons for the items in the corresponding order they were presented. A correct response increases the length of stimulus presented by one item (for each stimulus category), while an incorrect response decreases the length of the stimulus by one item. Each trial began with five stimuli and increased or decreased depending on the participants’ performance. The minimum length possible was one while the maximum was ten. Each test comprised of 25 trials with no time limit and without breaks between trials. Working memory ability was measured through the number of correct responses over total trials: scores ranged from 0 to 25, with the highest score representing superior working memory.

Positive and Negative Affect Scale (PANAS).

We used PANAS to assess the current mood/affective state of the participants with state/feeling-descriptive statements [ 32 ]. PANAS has ten PA statements e.g. interested, enthusiastic, proud, and ten NA statements e.g. guilty, nervous, hostile. Each statement was measured using a five-point Likert scale ranging from very slightly or not at all to extremely, and then totalled to form overall PA or NA score with higher scores representing higher levels of PA or NA. In the current study, the internal reliability of PANAS was good with a Cronbach’s alpha coefficient of .819, and .874 for PA and NA respectively.

Smartphone Addiction Scale (SAS)

SAS is a 33-item self-report scale used to examine participants’ smartphone addiction [ 33 ]. SAS contained six sub-factors; daily-life disturbance that measures the extent to which mobile phone use impairs one’s activities during everyday tasks (5 statements), positive anticipation to describe the excitement of using phone and de-stressing with the use of mobile phone (8 statements), withdrawal refers to the feeling of anxiety when separated from one’s mobile phone (6 statements), cyberspace-oriented relationship refers to one’s opinion on online friendship (7 statements), overuse measures the excessive use of mobile phone to the extent that they have become inseparable from their device (4 statements), and tolerance points to the cognitive effort to control the usage of one’s smartphone (3 statements). Each statement was measured using a six-point Likert scale from strongly disagree to strongly agree, and total SAS was identified by totalling all 33 statements. Higher SAS scores represented higher degrees of compulsive smartphone use. In the present study, the internal reliability of SAS was identified with Cronbach's alpha correlation coefficient of .918.

Phone conscious thought and perceived effect on learning

We included a one-item question for phone conscious thought: “During the memory test how often do you think of your smartphone?”. The aim of this question was two-fold; first was to capture endogenous interruption experienced by the separation, and second to complement the smartphone addiction to reflect current immediate experience. Participants rated this item on a scale of one (none to hardly) to seven (all the time). We also included a one-item question on how much they perceived their smartphone use has affected their learning and attention: “In general, how much do you think your smartphone affects your learning performance and attention span?”. This item was similarly rated on a scale of one (not at all) to seven (very much).

We randomly assigned participants to one of two conditions: low-phone salience (LS) and high-phone salience (HS). Participants were tested in groups of three to six people in a university computer laboratory and seated two seats apart from each other to prevent communication. Each group was assigned to the same experimental condition to ensure similar environmental conditions. Participants in the HS condition were asked to place their smartphone on the left side of the table with the screen facing down. LS participants were asked to hand their smartphone to the researcher at the start of the study and the smartphones were kept on the researcher’s table throughout the task at a distance between 50cm to 300cm from the participants depending on their seat location, and located out of sight behind a small panel on the table.

At the start of the experiment, participants were briefed on the rules in the experimental lab, such as no talking and no smartphone use (for HS only). Participants were also instructed to silence their smartphones. They filled in the consent form and demographic form before completing the PANAS questionnaire. They were then directed to CogLab software and began the working memory test. Upon completion, participants were asked to complete the PANAS again followed by the SAS, phone conscious thought, and their perception of their phone use on their learning performance and attention span. The researcher thanked the participants and returned the smartphones (LS condition only) at the end of the task.

Statistical analysis

We examined for normality in our data using the Shapiro-Wilk results and visual inspection of the histogram. For the normally distributed data, we analysed our data using independent-sample t -test for comparison between groups (HS or LS), paired-sample t test for within groups (e.g. before and after phone separation), and Pearson r for correlation. Non-normally distributed or ranked data were analysed using Spearman rho for correlation.

Preliminary analyses

Our female participants reported using their smartphone significantly longer than males, and so we examined the effects of gender on memory recall accuracy. We found no significant difference between males and females on memory recall accuracy, t (117) = .18, p = .86, Cohen’s d = .03. Subsequently, data were collapsed, analysed and reported on in the aggregate.

Smartphone presence and memory recall accuracy

An independent-sample t- test was used to examine whether participants’ performance on a working memory task was influenced by the presence (HS) or absence (LS) of their smartphone. Results showed that participants in the LS condition had higher accuracy ( M = 14.21, SD = 2.61) compared to HS ( M = 13.08, SD = 2.53), t (117) = 2.38, p = .02, Cohen’s d = .44 (see Fig 1 ). The effect size ᶇ 2 = .44 indicates that smartphone presence/salience has a moderate effect on participant working memory ability and a sensitivity power of .66.

https://doi.org/10.1371/journal.pone.0219233.g001

Relationship between Smartphone Addiction Score (SAS), higher phone conscious thought and memory recall accuracy

Sas and memory recal..

We first examined participants’ SAS scores between the two conditions. Results showed no significant difference between the LS (M = 104.64, SD = 24.86) and HS (M = 102.70, SD = 20.45) SAS scores, t (117) = .46, p = .64, Cohen’s d = .09. We predicted that those with higher SAS scores will have lower memory accuracy, and thus we examined the relationship between SAS and memory recall accuracy using Pearson correlation coefficient. Results showed that there was no significant relationship between SAS and memory recall accuracy, r = -.03, n = 119, p = .76. We also examined the SAS scores between the LS and HS groups on memory recall accuracy scores. In the LS group, no significant relationship was established between SAS score and memory accuracy, r = -.04, n = 58, p = .74. Similarly, there was no significant relationship between SAS score and memory accuracy in the HS group, r = .10, n = 61, p = .47. In the event that one SAS subscale may have a larger impact, we examined the relationship between each subscale and memory recall accuracy. Results showed no significant relationship between each sub-factor of SAS scores and memory accuracy, all p s > .12 (see Table 2 ).

https://doi.org/10.1371/journal.pone.0219233.t002

Phone conscious thought and memory accuracy.

We found a significant negative relationship between phone conscious thought and memory recall accuracy, r S = -.25, n = 119, p = .01. We anticipated a higher phone conscious thought for the LS group since their phone was kept away from them during the task and examined the relationship for each condition. Results showed a significant negative relationship between phone conscious thought and memory accuracy in the HS condition, r S = -.49, n = 61, p = < .001, as well as the LS condition, r S = -.27, n = 58, p = .04.

Affect/mood changes after being separated from their phone

We anticipated that our participants may have experienced either an increase in negative affect (NA) or a decrease in positive affect (PA) after being separated from their phone (LS condition).

We first computed the mean difference (After minus Before) for both positive ‘PA difference’ and negative affect ‘NA difference’. A repeated-measures 2 (Mood change: PA difference, NA difference) x 2 (Conditions: LS, HS) ANOVA was conducted to determine whether there is an interaction between mood change and condition. There was no interaction effect of mood change and condition, F (1, 117) = .38, p = .54, n p 2 = .003. There was a significant effect of Mood change, F (1, 117) = 13.01, p < .001, n p 2 = .10 (see Fig 2 ).

https://doi.org/10.1371/journal.pone.0219233.g002

Subsequent post-hoc analyses showed a significant decrease in participants’ positive affect before ( M = 31.12, SD = 5.79) and after ( M = 29.36, SD = 6.58) completing the memory task in the LS participants, t (57) = 2.48, p = .02, Cohen’s d = .28 but not for the negative affect, Cohen’s d = .07. A similar outcome was also shown in the HS condition, in which there was a significant decrease in positive affect only, t (60) = 3.45, p = .001, Cohen’s d = .37 (see Fig 2 ).

PA/NA difference on memory accuracy.

We predicted that LS participants will experience either an increase in NA and/or a decrease in PA since their smartphones were taken away and that this will affect memory recall negatively. Results showed that LS participants who experienced a higher NA difference had poorer memory recall accuracy ( r s = -.394, p = .002). We found no significant relationship between NA difference and memory recall accuracy for HS participants ( r s = -.057, p = .663, n = 61) and no significant relationship for PA difference in both HS ( r s = .217, p = .093) and LS conditions ( r s = .063, p = .638).

Relationship between phone conscious thought, smartphone addiction scale and mood changes to memory recall accuracy

Preliminary analyses were conducted to ensure no violation of the assumptions of normality, linearity, multicollinearity and homoscedasticity. There was a significant positive relationship between SAS scores and phone conscious thought, r S = .25, n = 119, p = .007. Using the enter method, we found that phone conscious thought explained by the model as a whole was 19.9%, R 2 = .20, R 2 Adjusted = .17, F (4, 114) = 7.10, p < .001. Phone conscious thought significantly predicted memory recall accuracy, b = -.63, t (114) = 4.76, p < .001, but not for the SAS score, b = .02, t (114) = 1.72, p = .09, PA difference score, b = .05, t (114) = 1.29, p = .20, and NA difference score, b = .06, t (114) = 1.61, p = .11.

Perception between phone usage and learning

For the participants’ perception of their phone usage on their learning and attention span, we found no significant difference between LS ( M = 4.22, SD = 1.58) and HS participants ( M = 4.07, SD = 1.62), t (117) = .54, p = .59, Cohen’s d = .09. There was also no significant correlation between perceived cognitive interference and memory accuracy, r = .07, p = .47.

We aimed [ 1 ] to examine the effect of smartphone presence on memory recall accuracy and [ 2 ] to investigate the relationship between affective states, phone conscious thought, and smartphone addiction to memory recall accuracy. For the former, our results were consistent with prior studies [ 11 – 13 ] in that participants had lower accuracy when their smartphone was next to them (HS) and higher accuracy when separated from their smartphones (LS). For the latter, we predicted that the short-term separation from their smartphone would evoke some anxiety, identified by either lower PA or higher NA post-test. Our results showed that both groups had experienced a decrease in PA post-test, suggesting that the reduced PA is likely to have stemmed from the prohibited usage (HS) and/or separation from their phone (LS). Our results also showed lower memory recall in the LS group who experienced higher NA providing some evidence that separation from their smartphone does contribute to feelings of anxiety. This is consistent with past studies in which participants reported increased anxiety over time when separated from their phones [ 14 ], or when smartphone usage was prohibited [ 17 ].

We also examined another variable–phone conscious thought–described in past studies [ 11 , 13 ], as a measure of smartphone addiction. Our findings showed that phone conscious thought is negatively correlated to memory recall in both HS and LS groups, and uniquely contributed 19.9% in our regression model. We propose that phone conscious thought is more relevant and meaningful compared to SAS as a measure of smartphone addiction [ 15 ] because unlike the SAS, this question can capture endogenous interruptions from their smartphone behaviour and participants were to simply report their behaviour within the last hour. The SAS is better suited to describe problematic smartphone use as the statements described behaviours over a longer duration. Further, SAS statements included some judgmental terms such as fretful, irritated, and this might have influenced participants’ ability in recalling such behaviour. We did not find any support for high smartphone addiction to low memory recall accuracy. Our participants in both HS and LS groups had similar high SAS scores, and they were similar to Kwon et al. [ 33 ] study, providing further evidence that smartphone addiction is relatively high in the student population compared to other categories such as employees, professionals, unemployed. Our participants’ high SAS scores and primary use of the smartphone was for social media signals potential problematic users [ 34 ]. Students’ usage of social networking (SNS) is common and the fear of missing out (FOMO) may fuel the SNS addiction [ 35 ]. Frequent checks on social media is an indication of lower levels of self-control and may indicate a need for belonging.

Our results for the presence of a smartphone and frequent phone conscious thought on memory recall is likely due to participants’ cognitive load ‘bandwidth effect’ that contributed to poor memory recall rather than a failure in their memory processes. Past studies have shown that participants with smartphones could generally perform simple cognitive tasks as well as those without, suggesting that memory failure in participants themselves to be an unlikely reason [ 1 , 3 , 5 ]. Due to our study design, we are unable to tease apart whether the presence of the smartphone had interfered with encoding, consolidation, or recall stage in our participants. This is certainly something of consideration for future studies to determine which aspects of memory processes are more susceptible to smartphone presence.

There are several limitations in our study. First, we did not ask the phone conscious thought at specific time points during the study. Having done so might have determined whether such thoughts impaired encoding, consolidating, or retrieval. Second, we did not include the simple version of this task as a comparison to rule out possible confounds within the sample. We did maintain similar external stimuli in their environment during testing, e.g. all participants were in one specific condition, lab temperature, lab noise, and thereby ruling out possible external factors that may have interfered with their memory processes. Third, the OS task itself. This task is complex and unfamiliar, which may have caused some disadvantages to some participants. However, the advantage of an unfamiliar task requires more cognitive effort to learn and progress and therefore demonstrates the limited cognitive load capacity in our brain, and whether such limitation is easily affected by the presence of a smartphone. Future studies could consider allowing participants to use their smartphone in both conditions and including eye-tracking measures to determine their smartphone attachment behaviour.

Implications

Future studies should look into the online learning environment. Students are often users of multiple electronic devices and are expected to use their devices frequently to learn various learning materials. Because students frequently use their smartphones for social media and communication during lessons [ 34 , 36 ], the online learning environment becomes far more challenging compared to a face-to-face environment. It is highly unlikely that we can ban smartphones despite evidence showing that students performed poorer academically with their smartphones presented next to them. The challenge is then to engage students to remain focused on their lessons while minimising other content. Some online platforms (e.g. Kahoot and Mentimeter) create a fun interactive experience to which students complete tasks on their smartphones and allow the instructor to monitor their performance from a computer. Another example is to use Twitter as a classroom tool [ 37 ].

The ubiquitous nature of the smartphone in our lives also meant that our young graduates are constantly connected to their smartphones and very likely to be on SNS even at work. Our findings showed that the most frequently used feature was the SNS sites e.g. Instagram, Facebook, and Twitter. Being frequently on SNS sites may be a challenge in the workforce because these young adults need to maintain barriers between professional and social lives. Young adults claim that SNS can be productive at work [ 38 ], but many advise to avoid crossing boundaries between professional and social lives [ 39 , 40 ]. Perhaps a more useful approach is to recognise a good balance when using SNS to meet both social and professional demands for the young workforce.

In conclusion, the presence of the smartphone and frequent thoughts of their smartphone significantly affected memory recall accuracy, demonstrating that they contributed to an increase in cognitive load ‘bandwidth effect’ interrupting participants’ memory processes. Our initial hypothesis that experiencing higher NA or lower PA would have reduced their memory recall was not supported, suggesting that other factors not examined in this study may have influenced our participants’ affective states. With the rapid rise in the e-learning environment and increasing smartphone ownership, smartphones will continue to be present in the classroom and work environment. It is important that we manage or integrate the smartphones into the classroom but will remain a contentious issue between instructors and students.

Acknowledgments

We would like to thank our participants for volunteering to participate in this study, and comments on earlier drafts by Louisa Lawrie and Su Woan Wo. We would also like to thank one anonymous reviewer for commenting on the drafts.

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29 May 2023

Episode 27: Our mobile world: How the cell phone is changing science and research

Subhra Priyadarshini

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A researcher documenting ant colonies. Credit: Subhra Priyadarshini

Does the mobile phone have a place in the lab?

The smartphone is a great example of technology leapfrog in countries like India, where a vast majority of phone users never had a landline. The increasing penetration of affordable mobile phones in developing countries is now making it possible for scientists to conduct meaningful and timely research, in the lab, field or while working from home.

Nature India's 'Our mobile world' podcast series will look at the many ways in which the smartphone has changed India’s science-society dynamics and the way researchers work. We will look at themes ranging from smartphones as enablers of science and research in India, to digital health, digital illiteracy, research around mobile phone e-waste, the gender digital divide and innovations in healthcare, medicine, agriculture and governance. We've chosen stories predominantly from India but also have examples from other counties in the global south.

Host: Subhra Priyadarshini, production and script: Aroma Warsi, sound editing: Prince George.

doi: https://doi.org/10.1038/d44151-023-00061-9

(Lightly edited for readability)

Speakers : Subhajit Bandyopadhyay, Preethi Jyothi, Jayashree Balasubramaniam, Subhra Priyadarshini

00:02 Support announcement : This episode is produced with support from DBT Wellcome Trust India Alliance.

00:30 Subhra Priyadarshini : The mobile phone. Yes, that’s the subject of our new podcast season. It’s ubiquitous, its indispensable, it’s almost like an extension of your hand. In many countries of the global south, such as India, the smartphone is a great example of technology leapfrog, as a vast majority of phone users never had a landline and were introduced to phones with the handheld phone.

And, of course, the increasing penetration of affordable mobile phones in developing countries is also making it possible for scientists to conduct meaningful and timely research, in the lab, in the field or while working from home, especially what we saw during the COVID-19 pandemic.

I am your host Subhra Priyadarshini, and in this new season of the Nature India podcast, I will explore how the mobile phone has changed India’s science-society dynamics as well as the way scientists, researchers and policy makers work. In today’s episode we will specifically look at smartphones as enablers of science and research. We will talk about the use of mobile phones for research and data collection, crowdsourcing and science education.

In short, does the lab have a place for the mobile phone? Let’s find out.

Up first, we talk of the use of mobile phones in a science laboratory setting. Convenient, right? When you don’t have a laptop handy. But can they also replace bulky, expensive scientific instruments in the lab or help set up labs, for instance, in remote places? We ask Subhajit Bandyopadhyay, a professor in the Department of Chemical Sciences at the Indian Institute of Science, Education and Research, Kolkata.

2:37 Subhajit Bandyopadhyay : Oh, yes, of course. A mobile phone can be used as a great tool, because it has so many features. I teach chemistry, and we deal with a lot of problems that are associated with chemistry. So quite often, you use instruments called spectrophotometers. And what it does is, it would tell you, very simplistically, a lot about the intensity of light and how it various wavelengths and so on. Typical spectrophotometric would be quite expensive. So if in village schools where you don't really have a stable power supply, and if the funding situation is not that great. We have developed programs, which could be used by schoolchildren, to supplement spectrophotometers. And they can do certain experiments like chemical kinetics and stuff with these cell phones. So it's basically free. And it's really easy to use. And, you know, the precision would not be as good as the spectrophotometer. But it's pretty good.

3:38 Subhra Priyadarshini : Right. And while mobile apps can provide easy access to scientific information, analysis, or simulations, or making learning and experimentation more engaging and accessible, imagine if you are colour blind or have impaired vision and can’t differentiate between all the colourful liquids in a chemistry lab. Subhajit and his team developed a smartphone app that helps colour-blind and visually impaired students detect colour change in a routine lab experiment, thereby ensuring their active participation and independence in the lab.

6:11 Subhajit Bandyopadhyay : We developed this a few years ago. About 8% of the male population of the world is colour blind. And about 0.5% of the female population of the world is colour blind. Now that's, that's really a big number. I'm thinking of a classroom of 80 students or, or sometimes in big colleges, it's over 100 students, you have a large number of students who are colour blind. Now, these students cannot really perform the chemistry experiments, because very often this chemistry experiments would involve colours. For example, the basic experiment of titration, acid base titration, or redox titration would involve colours. So what we did was we basically use this mobile phone camera and translated the colour data to something which was easy for a student with color blindness to perceive. For example, when the there is a change in the colour from colourless to red, the screen would indicate the colour change. At the same time, there will be other indicators like beeping sound, or it would vibrate.

Really was a very rewarding experience for me. So a few years ago, I went to Vietnam and one of the students told me that he was colour blind. And he said, he uses a particular programme that helps him greatly, and he takes out the phone and shows me my programme. So it was really a wonderful experience for me.

The application records the colour information. Hue Saturation and Value colour space and when there is a change in colour, it basically says there is a colour change by various means like beep sounds or vibration pulses.

6:11 Subhra Priyadarshini : One of Subhajit’s students Balraj Rathod, now a PhD scholar at the University of British Columbia in Canada, helped the team make this app.

Now, mobile phones have also emerged as supplementary teaching methods by providing access to educational resources, remote communication and multimedia learning. Preethi Jyothi, a faculty member in the Department of Computer Science at IIT Bombay uses it as a teaching aid.

6:53 Preethi Jyothi : So to give an example, smartphones now have lots of these built-in sensors. And using the sensors, you could teach fundamental concepts in physics, like, motion, and pressure, and so on. Typically abstract concepts, but using smartphones to make lab lessons applications involving these concepts would really reinforce the student's interest in learning,specific concepts. and also language learning. when you're trying to speak a new language, how to pronounce words, and so on, if you have apps on your smartphones, which will record what you're saying, and then give you instant feedback about how you're pronouncing certain words. That's a very powerful kind of tool. So I think science education, certainly mobile phones have a place.

7:35 Subhra Priyadarshini : And Preethi tell us a bit about the crowd sourced research, which has been your forte, along with your colleague Kameswari Chebrolu.

7:45 Preethi Jyothi : These days smartphones can also be used to gather data from people. And this could be because smartphones have GPS systems enabled, you could use it to gather data from people for various applications, like say traffic forecasting, or route planning and so on. I work on applying machine learning techniques for speech and language. And I'm specifically interested in building technologies for Indian languages. And so this app that we built that it's called clap, it's available on the Google Play Store. So this is an app via which you can be collected speech data from anyone who downloads this app. the volunteers would be asked to just read out these prompts. what we get immediately is parallel text with the corresponding speech from different speakers. unlike maybe other crowdsourcing platforms, which are very well known like Amazon's Mechanical Turk, and so on, which actually have many users from India, what we have found is that platforms like Mechanical Turk, most of the users are urban users, this automatically excludes a large fraction of users. Smartphones, now the reach is so much wider. And so our idea was to be able to reach users across a very broad spectrum, spanning multiple demographics they're all already very comfortable with using mobile phones. And this is currently a big area of interest across kind of machine learning technologies that you don't want to be catering just to very small sections of users. And if you're building machine learning applications, it all everything that is driving the accuracy of the such applications is the data that is being used to train these applications.That was the motivation behind building such an app on a smartphone so that we could get data from diverse users, and then use that to train speech recognition and language technologies.

9:40 Subhra Priyadarshini : Certainly, phones are the new trainers and teachers. They also play a crucial role in disseminating scientific knowledge for various end users. Take the instance of farmers as consumers of scientific knowledge. Jayashree Balasubramaniam, who works in the business of communication at Reliance Foundation tells us more.

10:06 Jayashree Balasubramaniam : The whole context of using mobile phones to bridge a number of gaps, I think that's something that's really picked up, especially post-COVID, where people have not only broken down their own personal barriers, but I think technology has grown immensely. What has also happened is that we see a large number of people, especially from communities, like small and marginal farmers, looking at ways in which they can explore this, take, for instance, you know, something that's related to crop practices, or, you know, pests and disease or a package of practices that developed by agricultural research institutions, and that's actually to be used by farmers. So what's been happening is that the typical agricultural extension services has managed to reach out to farmers through physical modes, but given the limitations that, you know, situations, such as the COVID pandemic brought in, what happened was that farmers also had to kind of look at other ways to gather the same information. During, you know, the 2020, I think this was the only sector in India that actually kind of had a positive growth. And this was primarily thanks to the way that they had, you know, kind of leveraged their knowledge.

11:27 Subhra Priyadarshini : Agriculture sciences have been a great beneficiary of mobile phone use for data collection and surveys, crowdsourcing, education and dissemination. We’ll, of course, dedicate a full episode to talk about this unique use case. But Jayashree, do talk us through a few of these use cases in this field as you have been at the forefront of this use.

11:53 Jayashree Balasubramaniam : Take for instance, you know, access to mobile-based advisories. Now, one of the biggest barriers in actually reaching information to a community like a small and marginal farmer has been internet connectivity or mobile connectivity, or actually just the use of technology, the ability to use technology,we work with millions of farmers across the country, when we actually need to send out a message, it's not just given to them in a simple localized context and format, it's also given in multiple languages. So, I think breaking the language barrier has been like one of you know, the most important steps in reaching this information, besides of course, the penetration in internet connectivity, The second is actually looking at ways in which with low mobile connectivity or low internet connectivity areas, you can use simple methods, these could be you know, chatbots this could be voice messages, this could also be some sort of audio conferencing that happens, where with a limited bandwidth and with a limited physical presence, you can still kind of get your message across, what we found through you know, our work in in a number of locations is that not only is the knowledge used, but you know, 75% or most of the farmers who have actually received these you know, pieces of information at different points of time have reported that they have actually improved their livelihoods.

13:18 Subhra Priyadarshini : And you see an easy uptake of this scientific information by people who may not have been exposed to science at all?

13:27 Jayashree Balasubramaniam : The second part of this whole process is adding to the scientific information with some sort of, you know, physical demonstration, new seed varieties, crop practices,water efficient , climate resilient, practices that can help rural communities.For instance, we're looking at something like Go. And DVIR are like a normalized difference vegetation index, which is you using, you know, satellite imagery.How it can predict something like drought or other crop stresses, even before that, it actually happens, it makes a big difference in actually transmitting this information. So this information is not just, you know, looked at, as somebody who's watching it, observing it, and recording it in a lab with the use of satellite imagery, this is actually getting translated through mobile or messaging or through, you know, mobile platforms, it's also like, you know, rural communities, we're using it for micro entrepreneurship and other things, but here translating the scientific information in simple, digestible nuggets, that has made a big difference to the way they actually adapt it on the field.

Now, we look at how integrated information like, weather, there is some sort of an impending natural disaster, you know, floods or cyclones, for instance, there are fishing communities who are actually exposing themselves to risk on a day to day basis,we found that 97% of the fishing communities were who actually received preventive information about the weather, said that actually, they not just, you know, minimize their losses, but actually, a lot of them were able to take preventive action to save their livelihood.

15:07 Subhra Priyadarshini : 10 years back Abhijit Pakhare, a community medicine specialist at the All India Institute of Medical Sciences at Bhopal and his colleagues analysed the use of mobile phones as research instruments for data collection in household surveys, clinical trials, surveillance and spatial data in global south countries. They inferred that mobile phones enabled economical, environment-friendly, faster and more accurate data collection for research. The limitations, however, were data entry errors, connectivity issues and of course the digital divide – all of which we will have a closer look at in our next episodes.

Ten years later, due to their widespread availability, affordability and connectivity, mobile phones are becoming extremely important to the process of science as much as science’s connect to society, as we have just heard through examples in the lab, in classrooms, in farming, fishing, rural communities. While urban users have to actually use apps for digital detox to keep away from potential negative effects of mobile use, science certainly benefits from these tiny devices. We will hear more on various aspects of scientific research benefitting from during this season.

Stay tuned, and give us a listen at your favourite podcast platform. This is Subhra Priyadarshini signing off from the Nature India podcast.

16:56 Support announcement : This episode was brought to you with support from DBT Wellcome Trust India Alliance.

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The impact of mobile phones on high school students: connecting the research dots

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Teens and Mobile Phones
Introduction: Why study mobile phones?

Acknowledgements
Chapter One: The basics of how teens acquire and use mobile phones
Chapter Two: How phones are used with friends – What they can do and how teens use them
Chapter Three: Attitudes towards cell phones
Chapter Four: How parents and schools regulate teens’ mobile phones

Introduction and background

Wireless communication has emerged as one of the fastest diffusing mediums on the planet, fueling an emergent “mobile youth culture”[6.numoffset=”6” Castells, M., Fernandez-Ardevol, M., Qiu, J., & Sey, A. (2007). Mobile communication and society: A global perspective . Cambridge, MA: MIT Press.] that speaks as much with thumbs as it does with tongues. At one of our focus groups a teen boy gushed, “I have unlimited texts . . . which is like the greatest invention of mankind.” His enthusiasm was hardly unique. Cell phone use and, in particular, the rise of texting has become a central part of teens’ lives. They are using their phones to stay in touch with friends and parents. They are using them to share stories and photos. They are using them to entertain themselves when they are bored. They are using them to micro-coordinate their schedules and face-to-face gatherings. And some are using their phones to go online to browse, to participate in social networks, and check their emails. This is the sunny side of the story. Teens are also using mobile phones to cheat on tests and to skirt rules at school and with their parents. Some are using their phones to send sexts, others are sleeping with buzzing phones under their pillows, and some are using their phones to place calls and text while driving.

While a small number of children get a cell phone in elementary school, the real tipping point for ownership is in middle school. About six in ten (66%) of all children in our sample had a cell phone before they turned 14. Slightly less than 75% of all high school students had a cell phone.

This report particularly highlights the rapid rise of text messaging in recent months. Some 72% of all US teens are now text message users, 1 up from 51% in 2006. Among them, the typical texter sends and receives 50 texts a day, or 1500 per month. By way of comparison a Korean, Danish or a Norwegian teen might send 15 – 20 a day and receives as many. Changes in subscription packages have encouraged widespread texting among US teens and has made them into world class texters. As a result, teens in America have integrated texting into their everyday routines. It is a way to keep in touch with peers even while they are engaged in other social activities. Often this is done discreetly and with little fuss. In other cases, it interrupts in-person encounters or can cause dangerous situations.

To understand the role that cell phones play in teens’ lives, the Pew Research Center’s Internet & American Life Project and Michigan’s Department of Communication Studies conducted a survey and focus groups in the latter part of 2009. The phone survey was conducted on landline and cell phones and included 800 youth ages 12-17 and one of their parents. It was administered from June 26-September 24, 2009. The overall survey has a margin of error of 4 percentage points; the portion dealing with teen cell owners involved 625 teens in the sample and has a margin of error of 4 percentage points; the portion dealing with teen texters involved 552 teens in the sample and has a margin of error of 5 percentage points.

A brief history of the mobile phone as a technology

The idea for cellular telephony originated in the US. The first cellular call and the first call from a hand held cellular device also were placed in the US.

The cell phone merges the landline telephony system with wireless communication. The landline telephone was first patented in 1876. Mobile radio systems have been used since the early 1900’s in the form of ship to shore radio, and were installed in some police cars in Detroit starting in 1921. The blending of landline telephone and radio communication came after the Second World War. The first commercially available “mobile radiophone service” that allowed calls from fixed to mobile telephones was offered in St. Louis in 1946. By 1964 there were 1.5 million mobile phone users in the US. 2 This was a non-cellular system that made relatively inefficient use of the radio bandwidth. In addition, the telephones were large, energy intensive car-mounted devices. According to communications scholar Thomas Farley, the headlights of a car would noticeably dim when the user was transmitting a call. 3

In the drive to produce a more efficient mobile telephone system, researchers W. Rae Young and Douglas Ring of Bell Labs developed the idea of cellular telephony, in which geographical areas are divided into a mesh of cells, each with its own cell tower. 4 This allowed a far more efficient use of the radio spectrum and the “cell” phones needed less power to send and receive a signal. The first installation was in 1969 on the Amtrak Metroliner that traveled between New York City and Washington. Four years later Martin Cooper of Motorola made the first cellular call from a prototype handheld cell phone.

Regulation around mobile phones

After the inauguration of mobile phone service in the US, a regulatory environment that allowed multiple mobile-calling standards stifled mobile communication development and expansion in the US for several years. Indeed, the growth of the GSM standard in Europe and the rise of DoCoMo in Japan meant that the dramatic developments in the cell phone industry were taking place abroad. In the US, small license areas for mobile phone companies meant that users were constantly roaming outside their core area. A user in Denver would have to pay roaming charges if he or she made or received a call in Ft. Collins, Colorado Springs or Vail. To the degree that texting was available, users could only text to users in their home network.

In the late 1980’s industry consolidation eliminated the small local areas and by the turn of the millennium, interoperability between operators became standard, and the cost of calling plans and the price of handsets fell. Rather than being a yuppie accessory, the cell phone became widely-used by everyone from the captains of industry and finance to the people who shined their shoes and walked their dogs.

As cell phones have become more available, they are increasingly owned and used by children and teens. Further, as handsets become more loaded with capabilities ranging from video recording and sharing, to music playing and internet access, teens and young adults have an ever-increasing repertoire of use. Indeed, we are moving into an era when mobile devices are not just for talking and texting, but can also access the internet and all it has to offer. This connectivity with others and with content has directed the regulator’s lens onto mobile safety practices. It has also prompted the beginning of a cultural conversation about how to ensure that parents have the tools to regulate their child’s mobile use, should they choose to. Understanding how youth use mobile phones is vital to creating effective policy based on the reality of how the technology is used. It is also important to understand how telecommunications company policies and pricing affect how teens and parents use their phones.

Previous research on cell phones and teens

This report tries to expand a tradition of cell phone research that extends into the early 1990s, 5 and work on landline telephony as far back as the 1970s. 6 The first studies to examine the social consequences of the mobile phone came in the early 1990s when researchers examined its impact on residential markets. 7 One of the earliest papers on cell phones examined it through the lens of gender; in 1993, Lana Rakow and Vija Navarro wrote about the cell phone and what they called “remote mothering.” 8 Starting in the mid 1990s in Europe there was the beginning of more extended scholarship on cellular communication, 9 and by 2000 work was being done in the US that evolved from a small number of articles to edited books and eventually to both popular and more scholarly books on mobile communication. 10

Several themes have been central in these analyses. One is the use of cell phones in the “micro-coordination” of daily interaction. 11 As the name implies, this line of research examines how the cell phone allows for a more nuanced form of coordination. Instead of having to agree on a time and place beforehand, individuals can negotiate the location and the timing of meetings as a situation clarifies itself. Micro-coordination can be used to organize get-togethers and it can be used to sort out the logistics of daily life (e.g. sending reminders to one another or exchanging information on the fly). Extending this concept further, the cell phone can be used to coordinate so called “flash mobs” as well as different kinds of protests. 12

While micro-coordination describes an instrumental type of interaction, another line of research has examined how the cell phone can be used for expressive interaction. Since the device provides us direct access to one another, it allows us to maintain ongoing interaction with family and friends. 13 This, in turn provides the basis for the enhancement of social cohesion. 14 In this vein, some researchers have examined how the cell phone affects our sense of safety and security. 15 The cell phone can be used to summon help when accidents have happened and they can be seen as a type of insurance in case something bad occurs. Others have examined how teens, as well as others, see the mobile phone as a form of self-expression. Having a cell phone is a status symbol and having a particularly sought after model can enhance our standing among peers. 16

Finally, focusing directly on teens, there has been considerable research on the role of the cell phone as part of the emancipation process. 17 Up to this point, however, there has been little quantitative analysis of teens in the US on this topic. 18 Indeed this is one of the main questions considered in this report. Before the cell phone, there were often discussions in the home as to whether a teen could have a landline extension in her room. Teens’ push to have their own landline phone underscored their drive to control contact with their peers. The rise of the cell phone has changed the dimensions of this discussion. The cell phone has provided teens with their own communication channel. This access can be used to plan and to organize daily life and it can be used to exchange jokes and endearments. It can also be used to plan mischief of varying caliber, and it can be used to exchange photos that are – literally – the picture of innocence or of depravity.

The organization of the report

This report is the fruit of a collaboration between the University of Michigan and the Pew Research Center’s Internet & American Life Project in an attempt to broadly capture the current state of mobile phone ownership and use among American youth and their families today. From June through September 2009, the Pew Internet Project fielded a random digit-dial telephone survey among a nationally representative sample of 800 teens ages 12-17 and one of their parents or a guardian (the teen and their parent/guardian were interviewed independently). In addition to the telephone survey, the University of Michigan fielded 9 focus groups among teens ages 12-18 in four cities in June and October of 2009. The focus groups queried teens more deeply about attitudes toward and practices around their mobile phone.

The study has been guided by a desire to measure the state of affairs around mobile phones and youth in the US – how many, how much, how often, with whom? – and to better understand how mobile phones fit into and enhance (or detract from) friendships and family relationships.

The report is organized into five chapters. The first chapter covers many of the basic measurements around mobile phones, the demographic variations around their use, and different models of phone ownership. This chapter also explores the economics of teens’ phone use, including payments, and calling and texting plan structures.

The second chapter of the report looks in depth at text messaging and voice calling, and compares the two modes of communication. It then places both of those activities in the broader context of teens’ overall communications practices as well as in the context of all the activities that teens can and do engage in on their mobile phone handsets, such as listening to music, sending email, looking up websites online and taking and sharing photos and videos.

The third chapter examines parents’ and teens’ attitudes towards their cell phones, and the ways the devices enhance and disrupt their lives. It details how families and teens feel about safety and the phone, and the ways in which the phone has become a social and entertainment hub. This chapter also explores how the phone has become an electronic tether between parents and children, and teens and friends, one so potent that teens frequently sleep with their phone under their pillows.

Chapter four examines the ways in which parents and schools regulate and monitor teens’ mobile phone use and how those actions may relate to teen cell phone-related behaviors.

The fifth chapter looks at teens, cell phones and “adverse behaviors.” It recaps some of our previous research on sexting and distracted driving, and presents new research on harassment through the mobile phone, as well as teens’ experiences with spam and the sending of regrettable text messages.

The last section of the report details the full set of methods that we used to conduct the research that undergirds this report.

Castells, M., Fernandez-Ardevol, M., Qiu, J., & Sey, A. (2007). Mobile communication and society: A global perspective . Cambridge, MA: MIT Press. ↩
This 72% of teens who text figure is slightly different than previous teens who text numbers that we have released. The difference lies in the question wording. For this question, we asked about teens texting friends, but we did not specify the platform (computer, cell phone) on which the texting was taking place. Our other teen texting number (66%) reflects teens who text on their own cell phone, and does not constrain who the teen may be texting with. Please see K9c and K20a in our questionnaire for exact question wording. ↩
Goggin, G. 2006. Cell phone culture: Mobile technology in everyday life. London: Routledge. ↩
Farley, T. 2005. “Mobile telephone history.” Telektronikk 3/4:22 – 34. ↩
Lindmark, S. 2002. “Evolution of techno-economic systems: An investigation of the history of mobile communications.” Doctoral Dissertation Thesis, Department of industrial management and economics, Chalmers University of Technology, Gothenberg, Sweden. ↩
Thanks to Fred Stutzman for his excellent literature review of this area. ↩
de Sola Pool, I. (Ed.). (1971). The social impact of the telephone. Cambridge: MIT press. Fischer, C. S. (1992). America Calling: A Social History of the Telephone to 1940. Berkeley, CA: University of California Press. ↩
Jarrat, J and Coates, J.F. (1990). ‘Future Use of Cellular Technology: Some Social Implications’, Telecommunications Policy, February 1990, pp 78–84. Lange, K. (1993). Some concerns about the future of mobile communications in residential markets. In M Christofferson (Ed.), Telecommunication: Limits to deregulation (pp. 197 – 210). Amsterdam: IOS Press. ↩
Rakow, L.F., & Navarro, V. (1993). Remote mothering and the parallel shift: Women meet the cellular telephone. Critical studies in mass communication , 10, 144-157. ↩
Haddon, L. (1996, 11.4.96). Mobile telephony issues: discussion paper for COST 248, Mobile sub-group. Paper presented at the COST 248 meeting, University of Sussex, Brighton, UK. Haddon, L. (1997). “Communications on the move: The Experience of Mobile Telephony in the 1990s.” Farsta:Telia. Ling, Rich. (1997). “One can talk about common manners!”: the use of mobile telephones in inappropriate situations. In Leslie Haddon (Ed.), Themes in mobile telephony: Final Report of the COST 248 Home and Work group . Stockholm: Telia. Ling, Rich, Julsrud, Tom and Krogh, Erling. (1998). The Goretex Principle: The Hytte and Mobile Telephones in Norway. In L. Haddon (Ed.), Communications on the Move: The Experience of Mobile Telephony in the 1990s ( COST248 Report). Farsta: Telia. ↩
Grinter, R. E. and Eldridge, M. A. (2001). y do tngrs luv 2 txt msg?. In ECSCW’01: Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work , Norwell, MA, USA, 2001 (pp. 219-238). Kluwer Academic Publishers. Katz, J. and Aakhus, M. (Eds.), 2002. Perpetual contact: Mobile communication, private talk, public performance. Cambridge: Cambridge University Press. ↩
Ling, R. and Yttri, B. (2002). Micro and hyper-coordination through the use of the mobile telephone. In Katz, J. and Aakhus, M. (Eds.), Perpetual contact: Mobile communication, private talk, public performance . Cambridge: Cambridge University Press. ↩
Rheingold, Howard. (2002) Smart Mobs: The Next Social Revolution . Perseus Publishing, Cambridge, MA. ↩
Licoppe, Christian. (2004). ‘Connected presence: the emergence of a new repertoire for managing social relationships in a changing communications technoscape.’ Environment and planning: Society and space, 22, 135 – 156. Christensen, T. H. (2009). ‘Connected presence’ in distributed family life. New Media & Society, 11(3), 433–451. ↩
Miyata, Kakuko, Boase, Jeffrey and Wellman, Barry. (2008). The Social Effects of Keitai and Personal Computer E-Mail in Japan. In Katz, J.E., Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Ling, Rich. (2008). New Tech, New Ties: How mobile communication is reshaping social cohesion. Cambridge: MIT Press. ↩
Ling, R. (2007). Children, youth, and mobile communication. Journal of Children and Media, 1(1), 60–67. Palfrey, J. and et. al. (December 31, 2008). Enhancing Child Safety and Online Technologies. Internet Safety Task Force. Retrieved January 10, 2009 from http://cyber.law.harvard.edu/pubrelease/isttf/ . Harris Interactive. (2008) A Generation Unplugged – Research Report. Harris Interactive. Accessed from http://files.ctia.org/pdf/HI_TeenMobileStudy_ResearchReport.pdf on January 10, 2009. Cox Communications (2009) Cox Communications Teen Online & Wireless Safety Survey, in Partnership with the National Center for Missing & Exploited Children® (NCMEC) and John Walsh. ↩
Fortunati, L. (2005). Mobile telephone and the presentation of self. In R. Ling & P. Pedersen (Eds.), Mobile Communications: Re-negotiation of the Social Sphere (pp. 203 – 218). London: Springer. Ito, M., Okabe, D., and Matsuda, M. 2005. Personal, portable, pedestrian: Mobile phones in Japanese life . Cambridge, MA: The MIT Press. Portus, Lourdes, 2008 How the Urban Poor Acquire and Give Meaning to the Mobile Phone in Katz, J.E. Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Katz, James E., Lever, Katie M., and Chen, Yi-Fan. 2008. Mobile Music as Environmental Control and Prosocial Entertainment. in Katz, J.E. Handbook of Mobile Communication Studies . Cambridge, MA: MIT Press. Harris Interactive. (2008) A Generation Unplugged – Research Report. Harris Interactive. Accessed from http://files.ctia.org/pdf/HI_TeenMobileStudy_ResearchReport.pdf on January 10, 2009. ↩
Ling, R. (2007). Children, youth, and mobile communication. Journal of Children and Media, 1(1), 60–67. ↩
On the Move: The Role of Cellular Communications in American Life. (2006). University of Michigan: Ann Arbor, MI. Accessed from http://itudcmc.files.wordpress.com/2010/03/onthemove1.pdf on March 24, 2010 ↩

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Studies find teens with problematic smartphone use are twice as likely to have anxiety

by King's College London

PSU (problematic smartphone use) describes a pattern of behaviors, thoughts and feelings linked to smartphones that resembles an addiction, such as feeling panicky or upset when the phone is unavailable, finding it difficult to control the amount of time spent on the phone, using it for longer without feeling satisfied, and using the phone to the detriment of other enjoyable or meaningful activities.

Researchers at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King's College London conducted two studies at schools investigating the association between PSU and mental health in young people. One study was with young people aged 16–18 years and the other was with 13–16 year-olds. These studies are among the first to evaluate PSU and mental health outcomes in adolescents.

Problematic smartphone use is linked to mental health

Overall, 18.7% of 16–18 year-olds and 14.5% of 13-16 year-olds self-reported PSU, with higher prevalence among girls.

Findings published in Acta Paediatrica revealed 16–18 year-olds who reported PSU were twice as likely to experience anxiety and almost three times as likely to experience depression compared to those who did not report PSU.

Findings published in BMJ Mental Health revealed nearly half of 13–16 year-olds with PSU reported symptoms of anxiety (44.4%) compared to 26.4% without PSU. Over half of 13–16 year-olds with PSU reported symptoms of depression (55.6%) compared to 35.8% without PSU.

This study also investigated if PSU was associated with mental health over time and showed increases in PSU scores over a four-week period were linked to increases in self-reported anxiety, depression and insomnia.

In the first study, conducted from January 31st to 8th March 2020, 657 16–18 year-olds completed assessments of PSU, anxiety, depression and insomnia. In the second, researchers measured PSU and changes in anxiety, depression and insomnia in 69 13–16 year-olds over a four-week period in 2022.

Many young people want to cut down time spent on smartphones

Both studies also found that many young people wish to spend less time on their phones. Almost two-thirds of 16–18 year-olds reported that they have tried to cut down on their smartphone use, and one in eight said they wanted help to reduce their use. Those with PSU were five times more likely to say they want help to cut down on their smartphone use compared to their peers without PSU.

Similarly, nearly 90% of 13–16 year-olds reported that they had attempted at least one strategy to limit their smartphone use, including putting it on silent or turning off notifications.

The researchers say the findings reveal that adolescents are aware that their smartphone use needs to be managed and are receptive to the idea of boundaries around use.

"Adolescent smartphone use is a huge concern for parents and caregivers. We found that problematic smartphone use was linked with anxiety, depression and insomnia across two separate adolescent age groups using two different research methods," says Professor Ben Carter.

"By revealing the link between problematic use of smartphones and poorer mental health , and demonstrating that young people are aware of this problem and are eager to manage their use, these studies highlight the need for evidence-based interventions to help adolescents struggling with difficult behaviors around their smartphone use."

Sixteen to 18 year-olds were recruited from five secondary schools across London, East-Midlands and South-West England; 13–16 year-olds were recruited from two secondary schools in London.

Distinction between smartphone use and screentime

In the first study, researchers also found TikTok and Instagram usage was higher among 16-18-year-olds who reported PSU, compared to those who did not. There was little difference in usage of WhatsApp, general gaming or general internet usage.

The study highlighted a distinction between PSU and screentime, described as the number of minutes spent on the smartphone rather than problematic behaviors surrounding its use. They found screentime was not associated with anxiety or depression in 16–18 year-olds, although did directly link to increased insomnia.

Strategies to reduce smartphone usage

Further analyses, also published by the researchers in Acta Paediatrica , revealed that putting their smartphone on "do not disturb," turning off notifications, and leaving the smartphone in another room at bedtime were reported to be the most effective strategies for reducing PSU.

In contrast, restricting access to specific apps, using a locked box during revision, and turning on grayscale were considered to be the least effective strategies.

"The good news is that adolescents are reflective and insightful about their use—they understand that smartphones bring downsides as well as benefits. Many young people in our studies employed reduction strategies, showing they are already taking active steps to manage their smartphone use," says Dr. Nicola Kalk.

"They found silent mode, removing notifications and placing the phone in another room at bedtime as the most effective. These are the same strategies which university students found helpful to reduce smartphone use.

"We hope these findings encourage parents and caregivers to have a conversation with their adolescents about their smartphone use which acknowledges both benefits and harms, and allows them to explore reasons why their adolescent might want to reduce their use, as well as the most effective tools to do so."

Ben Carter et al, 'There's more to life than staring at a small screen': a mixed methods cohort study of problematic smartphone use and the relationship to anxiety, depression and sleep in students aged 13–16 years old in the UK, BMJ Mental Health (2024). DOI: 10.1136/bmjment-2024-301115

Ben Carter et al, A multi‐school study in England, to assess problematic smartphone usage and anxiety and depression, Acta Paediatrica (2024). DOI: 10.1111/apa.17317

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Smartphone overuse: A hidden crisis in COVID-19

Zubair ahmed ratan.

a School of Health and Society, University of Wollongong, NSW, Australia

Sojib Bin Zaman

b Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia

Sheikh Mohammed Shariful Islam

c Institute for Physical Activity and Nutrition (IPAN), School of Exercise & and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia

Hassan Hosseinzadeh

The COVID-19 has interrupted normal activities and surfaced as the most significant health and economic challenges after the 2nd World War [1] . Most countries have imposed lockdown to break the chain of community transmission of this notorious virus, which has changed the way we are used to living in. Stay at home and work from home strategies are recommended worldwide as the most useful to prevent infection at both individual and community levels [2] . This self-isolation has encouraged people to turn to their smartphones to stay connected increasingly.

Smartphones forge opportunities for individuals to engage more in different online activities such as participating in social network sites, playing video games, surfing the web, and so on. A recent global survey showed that about 70 percent of internet users, especially the young generation worldwide, were using their smartphones or mobile phones more as a direct result of lockdown due to the coronavirus outbreak [3] . Such findings suggest that COVID-19 related lockdown policies might lead to the overuse or excessive usage of smartphones. Now, the question is whether overuse or excessive use of smartphones during the COVID period could develop particular harmful health issues and remain unchanged in the post-lockdown period. Smartphone overuse may lead to physical and psychological health, different musculoskeletal pain such as the neck, lower back, shoulder pain, depression, and anxiety [4] . This may result in the problematic use of smartphone [5] , which can hack the “reward system” of the brain to engage one in activities that s/he was employed during the lockdown period [6] . Thus, there is a high chance that subsequent harms will persist in the form of various mental health disorders, even if the lockdown effect is withdrawn.

The overusing pattern of smartphone involves a tendency to check notifications all the time. Such behaviour pattern can induce “reassurance seeking” pathway which broadly includes symptoms such as loneliness, low self-esteem, depression, and anxiety [7] . This reassurance-seeking behaviour is explainable with the theoretical model of ‘problematic mobile phone use’ suggested by Bilieux and colleagues [8] . Excessive use of smartphones may also affect sleep patterns by reducing rapid eye movement sleep, slow-wave sleep and consequently causing sleep deficiency. Excessive use of smartphones can potentially lead to gaming disorders and internet use disorders and eventually be considered to cause psychosocial crisis (i.e., sleep deprivation, stress, mood disorder and anxiety), which could be the aftermath of the COVID period [9] .

School students are also vulnerable, as one study suggested that 61% of parents classified their children as addicted to their smart devices for doing activities [10] . As educational institutions are temporarily closed, and school-children are passing their time at home or pursuing online classes, they can potentially be more exposed to using the internet and smart devices for their entertainment.

As countries are taking steps to relax lockdown, it is high time to identifying people who might have the problematic use of smartphones or other smart devices. First, we need a screening tool to identify people. Second, we require developing and implementing psychiatric intervention (e.g., establishing peer support). Third, though smartphone overuse currently is not an official diagnosis, the introduction of general health education services is required to reduce smartphone use. Therefore, health communication is required through the mass media to sensitise people about the problematic use of smartphone. For many users, problematic smartphone use might not pose a problem at all. Thus, without proper initiative, problematic smartphone usage can turn into an emerging public health challenge to annihilate lives by perpetuating the socio-psychological problems. It will be a crucial step to monitor smartphone overuse and take necessary action to minimise the problem through protective policies and family support during and after this COVID-19 pandemic.

Ethical approval

Not required.

Sojib Bin Zaman received a scholarship from the Australian Government research training program (RTP) in support of his academic career. This funding source had no role in the design, implementation, analyses, interpretation of the data, or decision to submit results.

Authors' statement

All authors equally contributed to prepare, review and approve the manuscript.

Declaration of Competing Interest

Authors declared no conflict of interest.

COMMENTS

Mobile phones: Impacts, challenges, and predictions
The mobile phone is stimulating one of the most important technological revolutions in human history. This article first presents impacts, challenges, and predictions of mobile phone use. It first indicates that the impact of the mobile phone on society has been predominantly positive while the mobile phone has certain negative attributes.
Smartphone use and academic performance: A literature review
1. Introduction. In 2018, approximately 77 percent of America's inhabitants owned a smartphone (Pew Research Center, 2018), defined here as a mobile phone that performs many of the functions of a computer (Alosaimi, Alyahya, Alshahwan, Al Mahyijari, & Shaik, 2016).In addition, a survey conducted in 2015 showed that 46 percent of Americans reported that they could not live without their ...
Smartphone Addiction and Associated Health Outcomes in Adult
Abstract. Background: Smartphones play a critical role in increasing human-machine interactions, with many advantages. However, the growing popularity of smartphone use has led to smartphone overuse and addiction. This review aims to systematically investigate the impact of smartphone addiction on health outcomes.
Mobile Phone Use and Mental Health. A Review of the Research That Takes
A formal systematic critical review with quality assessment of the papers was not done due to the large amount of included studies. The report presents an overview of the studies and examples of the main results. ... Towards a cross-cultural research in problematic mobile phone use. Addict. Behav. 2017; 64:275-280. doi: 10.1016/j.addbeh.2015. ...
Mobile phones: The effect of its presence on learning and memory
Research has shown that a mobile phone left next to the participant while completing a task, is a powerful distractor even when not in use [11,12]. Their findings showed that mobile phone participants could perform similarly to control groups on simple versions of specific tasks (e.g. visual spatial search, digit cancellation), but performed ...
The effects of smartphone addiction on learning: A meta-analysis
Overall, Table 2 shows that smartphone addiction was associated with statistically significant effect sizes. Under the fixed-effect model, there was a statistically significant difference between the weighted mean correlation of the dissertation (r = −0.26) and journal (r = −0.06).The between-levels difference was statistically significant, Q B (1) = 27.65, p < .001, and findings showed ...
A systematic review of smartphone-based human activity ...
Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous measurement of activities of daily living, making them especially well-suited for health research.
Cell-Phone Addiction: A Review
Abstract. We present a review of the studies that have been published about addiction to cell phones. We analyze the concept of cell-phone addiction as well as its prevalence, study methodologies, psychological features, and associated psychiatric comorbidities. Research in this field has generally evolved from a global view of the cell phone ...
Mobile phones: Impacts, challenges, and predictions
This paper focuses on the factors affecting consumer decision while buying a smart phone. The factors we consider here in this paper are battery life & capacity, fast charging, good quality ...
The smartphone as a tool for mobile communication research: Assessing
This article aims to describe the extent to which mobile methods can address some of the main challenges of mobile communication research. Mobile methods such as experience sampling involve "a naturalistic measurement approach in which human behavior is reported by an individual at multiple times over a period of days, weeks, or months" (Hedstrom and Irwin, 2017: 1).
Excessive Smartphone Use Is Associated With Health Problems in
Department of Behavioral Sciences, Ariel University, Ariel, Israel; Background and Aims: This present paper will review the existing evidence on the effects of excessive smartphone use on physical and mental health. Results: Comorbidity with depression, anxiety, OCD, ADHD and alcohol use disorder. Excessive smartphone use is associated with difficulties in cognitive-emotion regulation ...
Mobile phones: The effect of its presence on learning and memory
Our aim was to examine the effect of a smartphone's presence on learning and memory among undergraduates. A total of 119 undergraduates completed a memory task and the Smartphone Addiction Scale (SAS). As predicted, those without smartphones had higher recall accuracy compared to those with smartphones. Results showed a significant negative relationship between phone conscious thought ...
Smartphones at Work: A Qualitative Exploration of Psychological
In the field of mobile media research, extant research supported this argument by showing that people's mobile phone usage and dependency were associated with their psychological attributes (e.g., Butt & Phillips, 2008; Chittaranjan, Blom, & Gatica-Perez, 2011; Delevi & Weisskirch, 2013; Lane & Manner, 2011; Takao, 2014; Tosun & Lajunen, 2010).
Brain Drain: The Mere Presence of One's Own Smartphone Reduces
Smartphone Use and Conscious Distraction (the Orientation of Attention) Research on the relationship between mobile devices and cognitive functioning has largely focused on downstream consequences of device-related changes in the orientation of attention. For example, research on mobile device use while driving indicates that interacting with one's phone while behind the wheel causes ...
Cell phone addiction and psychological and physiological health in
Some studies also showed a positive relation of cell phone addiction and physiological health. The other school of thought reveals an indirect relation between cell phone usage and psychological health. They say adolescents use cell phones at night, which leads to insomnia. And insomnia ultimately results in depression, anxiety, and depression.
Mobile phone and base stations radiation and its effects on human
Men who carried a mobile phone on their belt and used it intensively during a five-day test period had a 19% decrease in high-mobility sperm (Kilgallon and Simmons, 2005). Men who talked on the phone for more than an hour a day had 17% fewer high-mobility sperm than men who talked on the phone for less than 15 min a day (Surendran et al., 2020).
"Mobile Phone Addiction: Symptoms, Impacts and Causes-A Review."
PDF | On Jan 21, 2019, Naik J. Reddy and others published "Mobile Phone Addiction: Symptoms, Impacts and Causes-A Review." | Find, read and cite all the research you need on ResearchGate
Episode 27: Our mobile world: How the cell phone is changing ...
We will look at themes ranging from smartphones as enablers of science and research in India, to digital health, digital illiteracy, research around mobile phone e-waste, the gender digital divide ...
(PDF) A Qualitative Study of The Perceived Impact of Mobile Phone
The current research considers the impact of mobile phone technology and social media use on cognitive function, and is extensive. Firstly, it is important to establish cognitive development as
(PDF) The impact of mobile phones on high school ...
attitudes towards the technological tool, be they positive or negative. To provide a detailed and comprehensive understanding of the impact of mobile phone. usage on high school students, we ...
Disposal of obsolete mobile phones: A review on replacement, disposal
The rapid innovation, technical changes and new product proliferation has turned the mobile phone industry into an extremely dynamic one (Cecere et al., 2015).As of April 2021, there were nearly 5.27 billion mobile phone users in the world ().The frequent launch of new mobile phone models by various mobile phone companies induces consumers' willingness to purchase a more advanced device, and ...
Introduction: Why study mobile phones?
This report tries to expand a tradition of cell phone research that extends into the early 1990s, 5 and work on landline telephony as far back as the 1970s. 6 The first studies to examine the ... Mobile telephony issues: discussion paper for COST 248, Mobile sub-group. Paper presented at the COST 248 meeting, University of Sussex, Brighton, UK. ...
Smartphones and Cognition: A Review of Research Exploring the Links
The research outlined in this paper lays a foundation on which a seemingly endless number of "next steps" can be imagined. There is an immense opportunity for additional research to be performed with the aim of giving psychologists and the world-at-large a better understanding the short-term and long-term effects of smartphone technology.
Studies find teens with problematic smartphone use are twice as likely
PSU (problematic smartphone use) describes a pattern of behaviors, thoughts and feelings linked to smartphones that resembles an addiction, such as feeling panicky or upset when the phone is ...
Smartphone overuse: A hidden crisis in COVID-19
Now, the question is whether overuse or excessive use of smartphones during the COVID period could develop particular harmful health issues and remain unchanged in the post-lockdown period. Smartphone overuse may lead to physical and psychological health, different musculoskeletal pain such as the neck, lower back, shoulder pain, depression ...
PDF Addiction to the Smartphone in High School Students: How It's in ...
mobile phone is not the source of addiction as such. Rather, it is the content which can be accessed through it what drives excessive use, as shown by other research on the matter (Beranuy et al., 2009; Sánchez-Carbonell et al., 2008). Theigh h use of mobile phones by young people has been predominant among female users, as a way to keep

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MINI REVIEW article

Introduction

Predictors of Excessive Smartphone-Use

Sensation Seeking and Boredom

Insecure Attachment, Poor Cognitive-Emotional Regulation and Communication Problems

Impaired Cognitive Function

Social Media Use and Personality

Comorbidity With Anxiety, Depression OCD, ADHD and Alcohol Use Disorder

Medical Complications- Sleep, Physical Fitness, Eyesight, Migraine and Pain

Brain Imaging

Author Contributions

Conflict of Interest

Supplementary Material

Mobile phones: The effect of its presence on learning and memory

Introduction

Present study

Materials and methods

Ethical approval and informed consent

Study design

Working memory span test.

Positive and Negative Affect Scale (PANAS).

Smartphone Addiction Scale (SAS)

Phone conscious thought and perceived effect on learning

Statistical analysis

Preliminary analyses

Smartphone presence and memory recall accuracy

Relationship between Smartphone Addiction Score (SAS), higher phone conscious thought and memory recall accuracy

Phone conscious thought and memory accuracy.

Affect/mood changes after being separated from their phone

PA/NA difference on memory accuracy.

Relationship between phone conscious thought, smartphone addiction scale and mood changes to memory recall accuracy

Perception between phone usage and learning

Implications

Acknowledgments

Episode 27: Our mobile world: How the cell phone is changing science and research

Does the mobile phone have a place in the lab?

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The impact of mobile phones on high school students: connecting the research dots

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72% of U.S. high school teachers say cellphone distraction is a major problem in the classroom

Research Topics

Studies find teens with problematic smartphone use are twice as likely to have anxiety

Problematic smartphone use is linked to mental health

Many young people want to cut down time spent on smartphones

Distinction between smartphone use and screentime

Strategies to reduce smartphone usage

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Timely responses—even from a car—drive babies' learning

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An estimated 1 in 4 children and young people have problematic smartphone usage

Day-long workshop in cognitive behavioral therapy found to effectively reduce depression in 16- to 18-year-olds

Investigating self-harm and digital technology overuse in young people with lived mental health experience

More than four hours of daily smartphone use associated with health risks for adolescents

Most teens report feeling happy or peaceful when they go without smartphones, Pew survey finds

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