Associations between Self-Reports and Device-Reports of Social Networking Site Use: An Application of the Truth and Bias Model

Burnell, Kaitlyn; George, Madeleine J.; Kurup, Allycen R.; Underwood, Marion K.; Ackerman, Robert A.

doi:10.1080/19312458.2021.1918654

Cited by 25 publications

(21 citation statements)

References 23 publications

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“…A recent meta-analysis found a modest correlation ( r = .38, 95% confidence interval = [.33, .42]) between self-reported and device-logged digital-technology use, which indicates “that self-report measures of media use may not be a valid stand-in for more objective measures” (Parry et al, 2021, p. 7). Furthermore, several studies have found that the error involved with self-reported digital-technology use is systematically related to crucial participant characteristics, such as gender or age (Ernala et al, 2020; vanden Abeele et al, 2013), volume of digital-technology use (Boase & Ling, 2013; Deng et al, 2019; Ernala et al, 2020; Sewall et al, 2020), and level of mental well-being (Burnell et al, 2021; Sewall et al, 2020; Sewall & Parry, 2021). Thus, given the focus on explicating the association between digital-technology use and psychological distress, it is likely that the self-reported digital-technology use data in the extant longitudinal analyses described above—and the subsequent findings and conclusions—are systematically biased by participant characteristics that are fundamental to the phenomenon under investigation.…”

mentioning

confidence: 99%

Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

Sewall

Goldstein

Wright

et al. 2022

Clinical Psychological Science

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Despite a plethora of research, the link between digital-technology use and psychological distress among young adults remains inconclusive. Findings in this area are typically undermined by methodological limitations related to measurement, study design, and statistical analysis. Addressing these limitations, we examined the prospective, within-persons associations between three aspects of objectively measured digital-technology use (duration and frequency of smartphone use, duration of social-media use) and three aspects of psychological distress (depression, anxiety, and social isolation) among a sample of young adults ( N = 384). Across 81 different model specifications, we found that most within-persons prospective effects between digital-technology use and psychological distress were statistically nonsignificant, and all were very small—even the largest effects were unlikely to register a meaningful impact on a person’s psychological distress. In post hoc subgroup analyses, we found scant evidence for the claim that digital-technology use is more harmful for women and/or younger people.

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mentioning

confidence: 99%

Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

Sewall

Goldstein

Wright

et al. 2022

Clinical Psychological Science

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“…As the pandemic situation has naturally impeded data collection from human subjects, much research has relied on survey data 57 . By combining objective tracking of activity, sleep and phone data, with participants' self-report through ecological momentary assessment, the current study provides longitudinal insights, while minimizing reporting biases associated with (retrospective) surveys responses 14,[58][59][60][61]…”

Section: Discussionmentioning

confidence: 99%

The influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening

Massar¹,

Ng²,

Cs³

et al. 2021

Preprint

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The COVID-19 pandemic imposed massive changes to daily lives worldwide. While lockdowns arrived abruptly, the continuation of social-distancing measures like working from home could have longer-term influences. We longitudinally tracked lifestyle behaviors (sleep/physical activity/phone use) and mental wellbeing through lockdown and reopening in Singapore. Earlier sleep and increased physical activity benefited from offices reopening for in-person work. However, this was offset by higher stress and poorer mood. Changes were proportional to the degree of hybrid work adoption. Counter to expectation, smartphone usage did not decrease after reopening, and usage around bedtime increased marginally. Cluster analysis showed that while heavier bedtime smartphone use was associated with later sleep initiation and lower physical activity, intermediate bedtime usage was associated with more favorable wellbeing indicators. As hybrid work arrangements and expanded e-device use will likely persist during the pandemic and its aftermath, our findings could inform strategies on adapting to new societal norms.

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“…Motivations for using user-donated data stem from limitations of other methods. People's perceptions of their own online behavior, for instance, can be unreliable [27,42,9,12]. Additionally, researcher-created accounts on digital platforms may lack the authenticity, diversity and history that real user accounts have.…”

Section: Data Donationmentioning

confidence: 99%

“…Due to TikTok's lack of external access (e.g., API) through which to conduct direct measurements, all of this research must be conducted with external data. Prior work has gathered data by scraping the platform (e.g., [2,19,20]), an approach that can only collect a few thousands of videos, relies on publicly available information that are included on the web page's source, and is usually biased towards popular videos; from self-reports (e.g., [18,22,26]), which suffer from known biases in social media research [27,42,9,12]; or from researcher-created accounts [6,35], which is a promising technique, but may yield data that ultimately lacks the authenticity, diversity, and account history that real user accounts would contain.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Rights of Data Subjects for Social Media Analysis: Studying TikTok via Data Donations

Zannettou¹,

Nemeth²,

Ayalon³

et al. 2023

Preprint

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TikTok is a relatively novel and widely popular media platform. In response to its expanding user base and cultural impact, researchers are turning to study the platform; however, TikTok, like many social media platforms, restricts external access to data. Prior works have acquired data from scraping the platform, user self-reports, and from accounts created by researchers for the study's purpose. Existing techniques, while yielding important insights, contain limitations for gathering large-scale quantitative insights on how real TikTok users behave on the platform. We bridge this research gap by implementing a data donation system to collect TikTok data. Our system leverages users' right to access their data enabled by the EU's GDPR regulation. We recruit 347 TikTok users, ask them to request their data from TikTok, and then use our system to customize, anonymize, and donate their data. We collect 4.9M videos viewed 9.2M times by our participants -and associated engagement metrics -to analyze how people consume content on TikTok, how prevalent liking behavior is on TikTok, and whether there are substantial differences across our participants' demographics. We conclude our work by discussing the lessons learned and future avenues for implementing data donation systems, which we believe offer a promising avenue for collecting user behavioral traces to understand social phenomena through the lens of the Web.

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Associations between Self-Reports and Device-Reports of Social Networking Site Use: An Application of the Truth and Bias Model

Cited by 25 publications

References 23 publications

Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

The influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening

Leveraging Rights of Data Subjects for Social Media Analysis: Studying TikTok via Data Donations

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