Evidence map›Paper›PMID 32161431›Full record

ArticleJournal of adolescent research2020

Screenomics: A New Approach for Observing and Studying Individuals' Digital Lives.

Nilam Ram, Xiao Yang, Mu-Jung Cho, Miriam Brinberg, Fiona Muirhead, Byron Reeves, Thomas N Robinson

Open access · bronzeAbstract read
In one paragraph

Article in Journal of adolescent research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
17.0field-weighted citation impact, top 1% of its field
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Nilam RamPennsylvania State University, University Park, PA, USA.
Xiao YangPennsylvania State University, University Park, PA, USA.
Mu-Jung ChoStanford University, Stanford, CA, USA.
Miriam BrinbergPennsylvania State University, University Park, PA, USA.
Fiona MuirheadUniversity of Strathclyde, Glasgow, Scotland, UK.
Byron ReevesStanford University, Stanford, CA, USA.
Thomas N RobinsonStanford University, Stanford, CA, USA.
Pennsylvania State University · USStanford University · USUniversity of Strathclyde · GB

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Psychosocial Determinants and Biological Pathway to Healthy Aging (Pathways)T32AG049676 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI LYNN M. MARTIRE · 2016 to 2026
$3.9M
Toward a Unifying Model of Self-Regulation and its DevelopmentR01HD076994 · NICHD · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLE, PAMELA M, RAM, NILAM · 2014 to 2019
$2.8M
Penn State Biomedical Big Data to Knowledge (B2D2K) Training ProgramT32LM012415 · NLM · PENNSYLVANIA STATE UNIVERSITY, THE · PI BROACH, JAMES R., HONAVAR, VASANT G. · 2016 to 2020
$1.2M
NCATS NIH HHS UL1 TR002014NIA NIH HHS T32 AG049676NICHD NIH HHS R01 HD076994NLM NIH HHS T32 LM012415
6 · The paper itself

Abstract

aimsThis study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach - SAMPLE: Over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14-15 years, from low-income, racial/ethnic minority neighborhoods.

methodScreenomes collected from smartphones for one to three months, as sequences of smartphone screenshots obtained every five seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human-labeling, and qualitative inquiry.

findingsAdolescents' digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations - with apps, food-related content, and sentiment as illustrative examples. IMPLICATIONS: We propose that the screenome provides the fine granularity of data needed to study individuals' digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development.

Indexed as

adolescencedigital mediaexperience samplingintensive longitudinal datascreenomescreenomicssmartphonesocial media

Identifiers

PMID32161431
PMCPMC7065687
OpenAlexW2986651361

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.