scholarly journals The Association Between Well-Being and Objectively Measured Versus Self-Reported Smartphone Time

2021 ◽  
Author(s):  
Lisa C. Walsh ◽  
Karynna Okabe-Miyamoto ◽  
Annie Regan ◽  
Jean Twenge ◽  
Sonja Lyubomirsky

Recent correlational research links smartphone and social media use to lower well-being among Gen Z youth, yet other work suggests that the effects are small and unnoteworthy. However, these findings rely heavily on self-report. How accurate is self-reported smartphone time and are objectively measured screen activities associated with lower well-being than nonscreen activities? Finally, are some smartphone uses “better” for well-being than others? We addressed these questions by examining correlations among psychosocial well-being and smartphone time in 414 Gen Z participants. Although objective smartphone use (i.e., assessed via Apple’s Screen Time function) and self-reports were correlated at r=.55, most participants were unable to accurately estimate their smartphone time. Furthermore, the more they used their smartphones—whether assessed objectively or via self-report—the less happy they were (rs=–.14 to .17). However, some apps were associated with more well-being (e.g., Camera, News, Snapchat) and others with less (e.g., Facebook, Reddit, Tinder, Twitter).

2019 ◽  
Author(s):  
Craig Sewall ◽  
Daniel Rosen ◽  
Todd M. Bear

The increasing ubiquity of mobile device and social media (SM) use has generated a substantial amount of research examining how these phenomena may impact public health. Prior studies have found that mobile device and SM use are associated with various aspects of well-being. However, a large portion of these studies relied upon self-reported estimates to measure amount of use, which can be inaccurate. Utilizing Apple’s “Screen Time” application to obtain actual iPhone and SM use data, the current study examined the accuracy of self-reported estimates, how inaccuracies bias relationships between use and well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 393 iPhone users, we found that: a.) participants misestimated their weekly overall iPhone and SM use by 22.1 and 16.6 hours, respectively; b.) the correlations between estimated use and well-being variables were consistently stronger than the correlations between actual use and well-being variables; and c.) the amount of inaccuracy in estimated use is associated with levels of participant well-being as well as amount of use. These findings suggest that estimates of device/SM use may be biased by factors that are fundamental to the relationships being investigated. **This manuscript is currently under review**


2021 ◽  
Author(s):  
Lizzy Winstone ◽  
Becky Mars ◽  
CMA Haworth ◽  
Jon Heron ◽  
Judi Kidger

Background There is mixed evidence as to the effects of different types of social media use on mental health, but previous research has been platform-specific and has focused on an oversimplified distinction between active and passive use. This study aimed to identify different underlying subgroups of adolescent social media user based on their pattern of social media activities and test associations between user type and future mental health. Methods Students from nineteen schools (N=2,456) in south-west England completed an online survey measuring thirteen social media activities and four psychosocial outcomes (past year self-harm, depression, anxiety and poor well-being) at age 13 years (October 2019) and repeated a year later (October 2020; aged 14 years). Latent class analysis using Mplus identified distinct classes of social media user. A bias-adjusted three-step model was used to test associations between class membership at baseline and mental health at follow-up. Analyses were adjusted for gender, ethnicity, sexual orientation, socio-economic status, disability, social media screen-time and baseline mental health.Results A four-class model of social media user at baseline was selected based on fit statistics and interpretability. User types were labelled High Communicators; Moderate Communicators; Broadcasters; and Minimal users. Broadcasters at age 13 had the poorest mental health outcomes at age 14, with mental health and well-being generally better in the two Communicator groups. Conclusions Findings suggest that adolescents with high levels of content sharing – in addition to socialising and browsing online – are most likely to be experiencing poor mental health a year later. Recommendations regarding social media use should move beyond screen-time to consider different user types, and mental health implications of their engagement with different online activities.


2021 ◽  
Author(s):  
Craig Sewall

IntroductionResearch indicates that stressors introduced by the COVID-19 pandemic have negatively impacted mental health, particularly among young people.1 Time spent on digital technology (e.g., social media, smartphones) has also increased2 as schools, workplaces, and social gathering sites have closed, thus intensifying pre-pandemic concerns regarding the putative effects of digital technology use (DTU) on mental health. Indeed, recent academic and newspaper articles have both directly and indirectly asserted that increased DTU is a source of the heightened psychological distress observed during the pandemic.3–5 However, these claims are dubious for two primary reasons. First, these articles rely on self-report measures of DTU, which are inaccurate6 and prone to systematic bias.7 Second, since the pandemic has impacted both mental health and DTU for many, the observed association between the two may be attributable to a shared common cause, rather than causality. Thus, we investigated the longitudinal associations between objectively measured DTU and mental health while accounting for important COVID-19-related effects.MethodsThis study was approved by the University of Pittsburgh and followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. In this four-wave panel study, participants were recruited from Prolific (https://www.prolific.co/), an online participant-recruitment platform. Waves of data collection were launched on August 14, September 12, October 14, and November 9 of 2020. Eligible participants were U.S. residents, 18-35 years old, iPhone users, and had ≥ 10 previous submissions on Prolific with approval rating ≥95%. At each wave, participants uploaded screenshots of their “Screen Time” application (which passively tracks device usage) and completed self-reports of mental health (depression, anxiety, suicidal ideation [SI]), COVID-19-related stressors, and perceived COVID-19-related impact on well-being and DTU (Table 1). We extracted three elements from the “Screen Time” screenshots: (1) total screen time, (2) total time spent on social media, and (3) total number of pickups. We estimated separate random-intercept multilevel models for each mental health outcome using Mplus. Predictors were entered hierarchically in blocks (see eTable 3 in Supplement) to assess ΔR2 at the within- and between-person levels. See Supplement for methodological details. ResultsA total of 384 young adults participated in this study (Mage = 24.5, SDage = 5.1; 57% female; 54% white; 48% Bachelor’s degree education or above). Overall, participants averaged 47.5 hours of Screen Time, 677 pickups, and 15.5 hours of social media over the past week. On average, participants reported experiencing between 4 and 5 pandemic-related stressors per wave. Mean depression and anxiety t-scores were 54.6 and 56.7, respectively, and nearly 29% of participants reported past-week SI at least once. See eTable 1 for summary statistics of sample demographics and primary variables.Results of the multilevel analyses revealed that objectively-measured total screen time and social media use were unrelated to within- or between-person differences in mental health, while between-person difference in pickups was negatively associated with depression (see Figure 1). Together, the objective DTU variables explained, at most, 2.8% of the within- or between-person variance in any of the mental health outcomes (eTable 3 in Supplement). COVID-related impacts on well-being had the largest effects across models—accounting for about 45% and 10%, respectively, of the between- and within-person variance in depression and anxiety, and 21%/28% of the between/within variance in SI. DiscussionAmong a sample of young adults, a population with particularly high rates of DTU8 and COVID-19-related distress,1 we found that objectively-measured DTU did not contribute to increases in depression, anxiety, or SI—refuting the popular notion that increases in DTU may be contributing to young peoples’ psychological distress during the pandemic. Rather, depression, anxiety, and SI were driven mostly by young peoples’ reports of the pandemic’s impact on their well-being. The convenience-based sample, retrospective (past week) assessments of mental health outcomes, and single-item measures of COVID-19-related impacts are limitations of the study. Nevertheless, results indicate that current speculations about the direct harms of DTU on mental health may be unfounded and risk diverting attention from a more likely cause: pandemic-related stressors.


2020 ◽  
Vol 11 ◽  
Author(s):  
Valentina Boursier ◽  
Francesca Gioia ◽  
Alessandro Musetti ◽  
Adriano Schimmenti

The outbreak of coronavirus disease 2019 (COVID-19) prompted people to face a distressing and unexpected situation. Uncertainty and social distancing changed people's behaviors, impacting on their feelings, daily habits, and social relationships, which are core elements in human well-being. In particular, restrictions due to the quarantine increased feelings of loneliness and anxiety. Within this context, the use of digital technologies has been recommended to relieve stress and anxiety and to decrease loneliness, even though the overall effects of social media consumption during pandemics still need to be carefully addressed. In this regard, social media use evidence risk and opportunities. In fact, according to a compensatory model of Internet-related activities, the online environment may be used to alleviate negative feelings caused by distressing life circumstances, despite potentially leading to negative outcomes. The present study examined whether individuals who were experiencing high levels of loneliness during the forced isolation for COVID-19 pandemic were more prone to feel anxious, and whether their sense of loneliness prompted excessive social media use. Moreover, the potentially mediating effect of excessive social media use in the relationship between perceived loneliness and anxiety was tested. A sample of 715 adults (71.5% women) aged between 18 and 72 years old took part in an online survey during the period of lockdown in Italy. The survey included self-report measures to assess perceived sense of loneliness, excessive use of social media, and anxiety. Participants reported that they spent more hours/day on social media during the pandemic than before the pandemic. We found evidence that perceived feelings of loneliness predicted both excessive social media use and anxiety, with excessive social media use also increasing anxiety levels. These findings suggest that isolation probably reinforced the individuals' sense of loneliness, strengthening the need to be part of virtual communities. However, the facilitated and prolonged access to social media during the COVID-19 pandemic risked to further increase anxiety, generating a vicious cycle that in some cases may require clinical attention.


2020 ◽  
Author(s):  
Laura Boeschoten ◽  
Irene Ingeborg van Driel ◽  
Daniel L. Oberski ◽  
J. Loes Pouwels

Since the introduction of social media platforms, researchers have investigated how the use of such media affects adolescents’ well-being. Thus far, findings have been inconsistent. The aim of our interdisciplinary project is to provide a more thorough understanding of these inconsistencies by investigating who benefits from social media use, who does not and why it is beneficial for one yet harmful for another. In this presentation, we explain our approach to combining social scientific self-report data with the use of deep learning to analyze personal Instagram archives.


2021 ◽  
Author(s):  
Lisa C. Walsh ◽  
Annie Regan ◽  
Karynna Okabe-Miyamoto ◽  
Sonja Lyubomirsky

Both scientists and laypeople have become increasingly concerned about smartphones, especially their associated digital media (e.g., email, news, gaming, and dating apps) and social media (e.g., Facebook, Instagram, Snapchat). Recent correlational research links substantial declines in Gen Z well-being to digital and social media use, yet other work suggests the effects are small and unnoteworthy. To further disentangle correlation from causation and better elucidate the strength and direction of effects, we conducted a pre-registered 8-day experimental deprivation study with Gen Z individuals (N = 338). Participants were randomly assigned to one of four conditions: (1) restrict digital media use, (2) restrict social media use, (3) restrict water use (active control), or (4) restrict nothing (measurement-only control). Relative to controls, participants restricting digital media reported a variety of benefits, including higher life satisfaction, mindfulness, autonomy, competence, and self-esteem, and reduced loneliness and stress. In contrast, those assigned to restrict social media reported relatively few benefits (increased mindfulness) and even some costs (more negative emotion).


2021 ◽  
Author(s):  
Niklas Johannes ◽  
Thuy-vy Thi Nguyen ◽  
Netta Weinstein ◽  
Andrew K Przybylski

There is a lively debate on the effects of social media use, shaped by self-reported measurements of social media use. However, self-reports have been shown to suffer from low accuracy compared to logged measures of social media use. Even though it is unclear how problematic that measurement error is for our inferences, many scholars call for the exclusive use of ‘objective’ measures. But if measurement error is not systematic, self-reports will still be informative. In contrast, if there is systematic error, associations between social media use and other variables, including well-being, are likely biased. Here, we report an exploratory five day experience sampling study among 96 participants (435 observations) to understand factors that could relate to low accuracy. First, we asked what stable individual differences are related to low accuracy. Second, we explored what daily states relate to accuracy. Third, we explored whether accuracy relates to well-being. Although we did find evidence for a systematic tendency to overestimate social media use, neither individual differences nor daily states were related to that tendency. Accuracy was also unrelated to well-being. Our results suggest that blindly calling for objective measures foregoes a responsibility to understand measurement error in social media use first.


2021 ◽  
pp. 183933492199886
Author(s):  
Kseniia Zahrai ◽  
Ekant Veer ◽  
Paul William Ballantine ◽  
Huibert Peter de Vries

With increasing concerns about problematic social media use, self-control is expected to become an effective approach for excessive users to decrease possible harm for their well-being. This article explores the current literature on the conceptualization of self-control on social media. For this, 25 papers from seven academic databases were analyzed in the chronological order in a systematic literature review. The sequence of applied frameworks demonstrates a gradual switch from theories of planned behavior to theories justifying non-planned behavior and self-control failures. This finding explains the emphasis of recent studies on the impulsive behavior of excessive social media users and the application of dual-system theories. However, research design of selected articles included mainly self-report tools to investigate impulsive self-control failures which may result in contradictory findings and deficient theoretical grounding for self-control interventions. All investigated papers claim a negative impact of social media self-control failures on personal well-being.


2018 ◽  
Vol 37 (10) ◽  
pp. 751-768 ◽  
Author(s):  
Melissa G. Hunt ◽  
Rachel Marx ◽  
Courtney Lipson ◽  
Jordyn Young

Introduction: Given the breadth of correlational research linking social media use to worse well-being, we undertook an experimental study to investigate the potential causal role that social media plays in this relationship. Method: After a week of baseline monitoring, 143 undergraduates at the University of Pennsylvania were randomly assigned to either limit Facebook, Instagram and Snapchat use to 10 minutes, per platform, per day, or to use social media as usual for three weeks. Results: The limited use group showed significant reductions in loneliness and depression over three weeks compared to the control group. Both groups showed significant decreases in anxiety and fear of missing out over baseline, suggesting a benefit of increased self-monitoring. Discussion: Our findings strongly suggest that limiting social media use to approximately 30 minutes per day may lead to significant improvement in well-being.


2021 ◽  
Author(s):  
Douglas A. Parry ◽  
Jacob T. Fisher ◽  
Hannah Mieczkowski ◽  
Craig Jeffrey Robb Sewall ◽  
Brittany I Davidson

Due to the methodological challenges inherent in studying social media use (SMU), as well as the methodological choices that have shaped research into the effects of SMU on well- being, clear conclusions regarding relationships between SMU and well-being remain elusive. We provide a review of five methodological developments poised to provide increased understanding in this domain: (1) the use of longitudinal and experimental designs; (2) the adoption of behavioural (rather than self-report) measures of SMU; (3) a shift away from aggregate use; (4) the emergence of an idiographic media effects paradigm; and (5) the use of formal modelling and machine learning. We focus on how these advances stand to bring us closer to understanding relations between SMU and well-being.


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