Evidence map›Paper›PMID 32636358›Full record

ReviewTranslational psychiatry2020

Designing m-Health interventions for precision mental health support.

N Bidargaddi, G Schrader, P Klasnja, J Licinio, S Murphy

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Translational psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 5 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

44 citing papers in PubMed, 5 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

5 authors.

N BidargaddiCollege of Medicine & Public Health, Flinders University, Adelaide, Australia. niranjan.bidargaddi@flinders.edu.au.ORCID http://orcid.org/0000-0003-2868-9260
G SchraderCollege of Medicine & Public Health, Flinders University, Adelaide, Australia.
P KlasnjaSchool of Information, University of Michigan, Ann Arbor, MI, USA.
J LicinioDepartments of Psychiatry, Pharmacology, Medicine and Neuroscience & Physiology, State University of New York Upstate Medical University, Syracuse, New York, USA.
S MurphyDepartments of Statistics & Computer Science, Harvard University, Boston, MA, USA.

Funding

Pilot, Mentoring, and Professional Development CoreP50DA039838 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI LI, RUNZE · 2015 to 2019
$13.9M
Data-Based Methods for Just-In-Time Adaptive Interventions in Alcohol UseR01AA023187 · NIAAA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MURPHY, SUSAN A · 2015 to 2019
$2.6M
NIAAA NIH HHS R01 AA023187NIDA NIH HHS P50 DA039838
6 · The paper itself

Abstract

Mobile health (m-Health) resources are emerging as a significant tool to overcome mental health support access barriers due to their ability to rapidly reach and provide support to individuals in need of mental health support. m-Health provides an approach to adapt and initiate mental health support at precise moments, when they are most likely to be effective for the individual. However, poor adoption of mental health apps in the real world suggests that new approaches to optimising the quality of m-Health interventions are critically needed in order to realise the potential translational benefits for mental health support. The micro-randomised trial is an experimental approach for optimising and adapting m-Health resources. This trial design provides data to construct and optimise m-Health interventions. The data can be used to inform when and what type of m-Health interventions should be initiated, and thus serve to integrate interventions into daily routines with precision. Here, we illustrate this approach in a case study, review implementation issues that need to be considered while conducting an MRT, and provide a checklist for mental health m-Health intervention developers.

Indexed as

Mental HealthTelemedicineHumans

Identifiers

PMID32636358
PMCPMC7341865

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.