Evidence map›Paper›PMID 28855245›Full record

ReviewEvidence-based mental health2017

The promise of digital mood tracking technologies: are we heading on the right track?

Gin S Malhi, Amber Hamilton, Grace Morris, Zola Mannie, Pritha Das, Tim Outhred

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Evidence-based mental health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 4 pooled it
–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

28 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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.

Gin S MalhiAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.
Amber HamiltonAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.
Grace MorrisAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0003-3598-9712
Zola MannieAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.
Pritha DasAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.
Tim OuthredAcademic Department of Psychiatry, Northern Sydney Local Health District, Sydney, New South Wales, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing understanding that mood disorders are dynamic in nature and fluctuate over variable epochs of time has compelled researchers to develop innovative methods of monitoring mood. Technological advancement now allows for the detection of minute-to-minute changes while also capturing a longitudinal perspective of an individual's illness. Traditionally, assessments of mood have been conducted by means of clinical interviews and paper surveys. However, these methods are often inaccurate due to recall bias and compliance issues, and are limited in their capacity to collect and process data over long periods of time. The increased capability, availability and affordability of digital technologies in recent decades has offered a novel, non-invasive alternative to monitoring mood and emotion in daily life. This paper reviews the emerging literature addressing the use of digital mood tracking technologies, primarily focusing on the strengths and inherent limitations of using these new methods including electronic self-report, behavioural data collection and wearable physiological biosensors. This developing field holds great promise in generating novel insights into the mechanistic processes of mood disorders and improving personalised clinical care. However, further research is needed to validate many of these novel approaches to ensure that these devices are indeed achieving their purpose of capturing changes in mood.

Indexed as

Mobile ApplicationsBipolar DisorderHumansMonitoring, PhysiologicMood DisordersTelemedicineHealth InformaticsInformation TechnologyMental HealthPsychiatry

Identifiers

PMID28855245
PMCPMC10516397

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.