Evidence map›Paper›PMID 27922603›Full record

ArticleMolecular psychiatry2017

Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies.

N Bidargaddi, P Musiat, V-P Makinen, M Ermes, G Schrader, J Licinio

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular psychiatry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 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

6 authors.

N BidargaddiSchool of Medicine, Flinders University, Adelaide, SA, Australia.
P MusiatSchool of Medicine, Flinders University, Adelaide, SA, Australia.
V-P MakinenSouth Australian Health and Medical Research Institute, Adelaide, SA, Australia.
M ErmesSchool of Medicine, Flinders University, Adelaide, SA, Australia.
G SchraderSchool of Medicine, Flinders University, Adelaide, SA, Australia.
J LicinioSchool of Medicine, Flinders University, Adelaide, SA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital footprints, the automatically accumulated by-products of our technology-saturated lives, offer an exciting opportunity for psychiatric research. The commercial sector has already embraced the electronic trails of customers as an enabling tool for guiding consumer behaviour, and analogous efforts are ongoing to monitor and improve the mental health of psychiatric patients. The untargeted collection of digital footprints that may or may not be health orientated comprises a large untapped information resource for epidemiological scale research into psychiatric disorders. Real-time monitoring of mood, sleep and physical and social activity in a substantial portion of the affected population in a naturalistic setting is unprecedented in psychiatry. We propose that digital footprints can provide these measurements from real world setting unobtrusively and in a longitudinal fashion. In this perspective article, we outline the concept of digital footprints and the services and devices that create them, and present examples where digital footprints have been successfully used in research. We then critically discuss the opportunities and fundamental challenges associated digital footprints in psychiatric research, such as collecting data from different sources, analysis, ethical and research design challenges.

Indexed as

Electronic Health RecordsHumansMental DisordersMental HealthPsychotherapy

Identifiers

PMID27922603
PMCPMC5285463

What OpenQuestion holds

Textmetadata
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.