Evidence map›Paper›PMID 39730518›Full record

ArticleScientific reports2024

Appnome analysis reveals small or no associations between social media app-specific usage and adolescent well-being.

Yuning Liu, Laura Marciano

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yuning LiuDepartment of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID 0000-0002-0513-4011
Laura MarcianoLee Kum Sheung Center for Health and Happiness, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA. lmarciano@hsph.harvard.edu.ORCID 0000-0002-8034-3227

Funding

Bidirectional Influences Between Adolescent Social Media Use and Mental HealthR21HD115354 · NICHD · HARVARD SCHOOL OF PUBLIC HEALTH · PI MARCIANO, LAURA · 2023 to 2023
$375k
National Institutes of Health (NIH)/National Institute of Mental Health (NIMH) 1R21HD115354-01NICHD NIH HHS R21 HD115354Swiss National Science Foundation P500PS_202974
6 · The paper itself

Abstract

The debate on how social media use (SMU) influences adolescent well-being is mostly based on self-reports of SMU. By collecting data and screenshots donated from 374 Swiss adolescents (Meanage = 15.71; SDage = 0.82) over 2 weeks, we created "Appnomes"-app-specific usage metrics on screentime, number of activations, and number of notifications per participant per day derived, and associated them with daily hedonic and eudaimonic well-being. Longer TikTok time predicted lower eudaimonic well-being (β = - 0.08) daily but higher positive emotions (β = 0.06) the next day; longer use of WhatsApp predicted negative emotions (β = 0.06) while more screen activations for WhatsApp predicted greater feelings of connection (β = 0.08). Instagram notification was positively related to increased feeling of focused (β = 0.06) the next day. YouTube screen unlocks predicted more feeling of meaning (β = 0.07) the next day. More Snapchat screentime predicted less relaxed, less competent, and less positive emotions (with - 0.07 < β < - 0.06). Results pointed towards minimal or no effects, challenging the moral panic on the detrimental impact of SMU on teen well-being.

Indexed as

EmotionsMobile ApplicationsSocial MediaAdolescentAdolescent BehaviorFemaleHumansMaleSwitzerlandAdolescentsLongitudinalScreenshotSocial media useTemporalityWell-being

Identifiers

PMID39730518
PMCPMC11681177

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.