Evidence map›Paper›PMID 31518298›Full record

ArticleJMIR pediatrics and parenting2018

Exploring the Transition to Fatherhood: Feasibility Study Using Social Media and Machine Learning.

Samantha J Teague, Adrian Br Shatte

Abstract read
In one paragraph

Article in JMIR pediatrics and parenting, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Samantha J Teague *Centre for Social and Early Emotional Development, School of Psychology, Deakin University, Burwood, Australia.ORCID http://orcid.org/0000-0002-0487-7307
Adrian Br Shatte *Centre for Social and Early Emotional Development, School of Psychology, Deakin University, Burwood, Australia.ORCID http://orcid.org/0000-0002-6225-9697

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFathers' experiences across the transition to parenthood are underreported in the literature. Social media offers the potential to capture fathers' experiences in real time and at scale while also removing the barriers that fathers typically face in participating in research and clinical care.

objectiveThis study aimed to assess the feasibility of using social media data to map the discussion topics of fathers across the fatherhood transition.

methodsDiscussion threads from two Web-based parenting communities, r/Daddit and r/PreDaddit from the social media platform Reddit, were collected over a 2-week period, resulting in 1980 discussion threads contributed to by 5853 unique users. An unsupervised machine learning algorithm was then implemented to group discussion threads into topics within each community and across a combined collection of all discussion threads.

resultsResults demonstrated that men use Web-based communities to share the joys and challenges of the fatherhood experience. Minimal overlap in discussions was found between the 2 communities, indicating that distinct conversations are held on each forum. A range of social support techniques was demonstrated, with conversations characterized by encouragement, humor, and experience-based advice.

conclusionsThis study demonstrates that rich data on fathers' experiences can be sourced from social media and analyzed rapidly using automated techniques, providing an additional tool for researchers exploring fatherhood.

Indexed as

fathersinfodemiologyparent-child relationsparentingperinatal caresocial mediaunsupervised machine learning

Identifiers

PMID31518298
PMCPMC6715057

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.