Dynamics of adolescents’ smartphone use and well-being are positive but ephemeral

Marciano, Laura; Driver, Charles C.; Schulz, Peter; Camerini, Anne-Linda

doi:10.1038/s41598-022-05291-y

Cited by 36 publications

(25 citation statements)

References 92 publications

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“…EMAs aim to minimize retrospective recall biases of traditional survey methods ( Torous et al, 2014 ), maximize ecological validity ( Russell and Gajos, 2020 ) by capturing human behavior in natural contexts, and study microprocesses ( Shiffman et al, 2008 ) in real-time. Additionally, both trace data and EMAs, or their combination ( Marciano et al, 2022 ), enable to model changes that happen at the individual level, thus allowing to overcome the Simpson’s paradox, for which the sign of a relationship observed in a population could become the opposite within the individuals ( Kievit et al, 2013 ).…”

Section: Mobile Approaches To Passively and Actively Collect Datamentioning

confidence: 99%

Reinventing mental health care in youth through mobile approaches: Current status and future steps

Marciano

Saboor²

2023

Front. Psychol.

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In this perspective, we aim to bring together research on mobile assessments and interventions in the context of mental health care in youth. After the COVID-19 pandemic, one out of five young people is experiencing mental health problems worldwide. New ways to face this burden are now needed. Young people search for low-burden services in terms of costs and time, paired with high flexibility and easy accessibility. Mobile applications meet these principles by providing new ways to inform, monitor, educate, and enable self-help, thus reinventing mental health care in youth. In this perspective, we explore the existing literature reviews on mobile assessments and interventions in youth through data collected passively (e.g., digital phenotyping) and actively (e.g., using Ecological Momentary Assessments—EMAs). The richness of such approaches relies on assessing mental health dynamically by extending beyond the confines of traditional methods and diagnostic criteria, and the integration of sensor data from multiple channels, thus allowing the cross-validation of symptoms through multiple information. However, we also acknowledge the promises and pitfalls of such approaches, including the problem of interpreting small effects combined with different data sources and the real benefits in terms of outcome prediction when compared to gold-standard methods. We also explore a new promising and complementary approach, using chatbots and conversational agents, that encourages interaction while tracing health and providing interventions. Finally, we suggest that it is important to continue to move beyond the ill-being framework by giving more importance to intervention fostering well-being, e.g., using positive psychology.

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Section: Mobile Approaches To Passively and Actively Collect Datamentioning

confidence: 99%

Reinventing mental health care in youth through mobile approaches: Current status and future steps

Marciano

Saboor²

2023

Front. Psychol.

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“…Besides investigating how personality manifests in smartphone-mediated daily behaviors, researchers have also been interested how smartphone use is related, for example, to affective well-being. Marciano et al (2022) looked for reciprocal dynamics between the frequency of smartphone use and time spent on the device and adolescents' self-reported daily well-being over 45 days. They found, among other things, that more frequent and longer smartphone use was related to higher well-being and that higher levels of well-being, in turn, were associated with longer subsequent smartphone use.…”

Section: Daily Behaviorsmentioning

confidence: 99%

“…They found, among other things, that more frequent and longer smartphone use was related to higher well-being and that higher levels of well-being, in turn, were associated with longer subsequent smartphone use. Comparing changes in affective well-being with changes in frequency and duration of smartphone use, they found that the former lasted longer (Marciano et al, 2022).…”

Section: Daily Behaviorsmentioning

confidence: 99%

Mobile Sensing Methods

Mehl¹,

Schoedel

2023

Preprint

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Mobile and wearable devices are equipped with an array of embedded digital sensors that produce continuous steams of digital trace data. These now effectively ubiquitous digital trace data can empower psychologists to study human behavior “in vivo” and “in situ,” which has been an important goal following the American Psychology Association’s “Decade of Behavior” (2000-2009). As a result, there is currently great excitement among psychological scientists about the potentials that sensor-based mobile technologies offer for studying everyday situations and behavior ecologically and at scale. This novel approach to field research is commonly referred to as mobile sensing, or passive sensing. In this chapter we retrace mobile sensing’s journey in social and personality psychology. We begin with briefly reviewing forces that helped pave the way for mobile sensing’s warm welcome in the field. In the second and third part, we provide an overview of the current use of mobile sensing in social and personality psychology and convey a very basic how-to. Finally, we end the chapter with a discussion of where we think mobile sensing currently stands and identify some possible future directions.

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“…In the past few years, several research groups have tried to resolve the inconsistency in the social media well-being literature by adopting a person-specific or idiographic media effects approach (Griffioen et al, 2021;Marciano et al, 2022;). An idiographic media effects approach involves the in-depth understanding of the effects of (social) media use on each single person.…”

Section: Affects Themmentioning

confidence: 99%

In Their Own Words: How Adolescents Differ in Their Social Media Use and How it Affects Them

Wal¹,

Valkenburg²,

Driel³

2022

Preprint

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Despite a burgeoning literature into the relationship between social media use (SMU) and adolescent well-being, clear conclusions about this relationship remain elusive as the literature has yielded a mixed bag of results. The aim of this study is to take a qualitative approach to improve our understanding of individual differences in (a) adolescents’ motives for using SMU, (b) their social media-related mood management, and (c) the effects they experience due to SMU. Based on eight focus groups among 55 adolescents ranging in age from 14 to 17 years, we found considerable homogeneity in adolescents’ motives to turn to social media. But we also found substantial heterogeneity in the moods that predict their SMU, their affective responses to SMU, and the effects they experienced due to SMU. Such sizeable individual differences may, in part, explain the inconsistent results in earlier quantitative work. We end with three lessons for future self-report studies.

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Dynamics of adolescents’ smartphone use and well-being are positive but ephemeral

Cited by 36 publications

References 92 publications

Reinventing mental health care in youth through mobile approaches: Current status and future steps

Reinventing mental health care in youth through mobile approaches: Current status and future steps

Mobile Sensing Methods

In Their Own Words: How Adolescents Differ in Their Social Media Use and How it Affects Them

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