Evidence map›Paper›PMID 41068178›Full record

ArticleScientific reports2025

Active night-time tweeting is associated with meaningfully lower mental wellbeing in a UK birth cohort study.

Daniel Joinson, Claire M A Haworth, Edwin Simpson, Nello Cristianini, Nina H Di Cara, Oliver S P Davis

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Daniel JoinsonSchool of Engineering Mathematics and Technology, University of Bristol, Bristol, UK. d.i.joinson@gmail.com.
Claire M A HaworthSchool of Psychological Science, University of Bristol, Bristol, UK.
Edwin SimpsonSchool of Engineering Mathematics and Technology, University of Bristol, Bristol, UK.
Nello CristianiniDepartment of Computer Science, University of Bath, Bath, UK.
Nina H Di CaraSchool of Psychological Science, University of Bristol, Bristol, UK.
Oliver S P DavisDepartment of Population Health Sciences (Bristol Medical School), MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Funding

CLOSER ES/K000357/1Engineering and Physical Sciences Research Council EP/N510129/1Engineering and Physical Sciences Research Council EP/S023704/1Wellcome Trust
6 · The paper itself

Abstract

It has been suggested that use of social media late at night could lead to worse mental health outcomes. We linked Twitter ('X') data to self-reported measures of mental health from the Avon Longitudinal Study of Parents and Children. We aimed to predict these measures from the average hour a participant posted Tweets. We used data from 310 adult participants and 18,288 Tweets. We found strong evidence the average hour participants posted Tweets was associated with depressive symptoms, anxiety symptoms, and mental wellbeing. Average hour explained almost 2% of the variation in mental wellbeing, comparable to reports of the impact of binge drinking and exercise. Participants who, on average, Tweeted through the night (23:00 to 05:00) showed meaningfully worse mental wellbeing than those who Tweeted during the daytime. Although the average hour that a participant posted their Tweets explained less of the variation in their depressive (0.2%) and anxiety (0.7%) symptoms, after stratification by age and sex these relationships became stronger. Our results could inform behavioural interventions for improving the safety of social media platforms.

Indexed as

AnxietyDepressionMental HealthSocial MediaAdolescentAdultBirth CohortFemaleHumansLongitudinal StudiesMaleMiddle AgedSelf ReportUnited KingdomYoung Adult

Identifiers

PMID41068178
PMCPMC12511309

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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 OpenQuestion graph.