Evidence map›Paper›PMID 35353053›Full record

ReviewJMIR mental health2022

The Current State and Validity of Digital Assessment Tools for Psychiatry: Systematic Review.

Nayra A Martin-Key, Benedetta Spadaro, Erin Funnell, Eleanor Jane Barker, Thea Sofie Schei, Jakub Tomasik, Sabine Bahn

Abstract readReview
In one paragraph

Review in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 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

35 citing papers in PubMed, 1 synthesis or guideline 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

7 authors.

Nayra A Martin-Key *Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-9731-3809
Benedetta Spadaro *Cambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-4654-1449
Erin FunnellCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-7652-8528
Eleanor Jane BarkerUniversity of Cambridge Medical Library, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0001-5472-2496
Thea Sofie ScheiPsyomics Ltd, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-0063-9707
Jakub TomasikCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0002-2127-4487
Sabine BahnCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-4690-6302

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the role digital technologies are likely to play in the future of mental health care, there is a need for a comprehensive appraisal of the current state and validity (ie, screening or diagnostic accuracy) of digital mental health assessments.

objectiveThe aim of this review is to explore the current state and validity of question-and-answer-based digital tools for diagnosing and screening psychiatric conditions in adults.

methodsThis systematic review was based on the Population, Intervention, Comparison, and Outcome framework and was carried out in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. MEDLINE, Embase, Cochrane Library, ASSIA, Web of Science Core Collection, CINAHL, and PsycINFO were systematically searched for articles published between 2005 and 2021. A descriptive evaluation of the study characteristics and digital solutions and a quantitative appraisal of the screening or diagnostic accuracy of the included tools were conducted. Risk of bias and applicability were assessed using the revised tool for the Quality Assessment of Diagnostic Accuracy Studies 2.

resultsA total of 28 studies met the inclusion criteria, with the most frequently evaluated conditions encompassing generalized anxiety disorder, major depressive disorder, and any depressive disorder. Most of the studies used digitized versions of existing pen-and-paper questionnaires, with findings revealing poor to excellent screening or diagnostic accuracy (sensitivity=0.32-1.00, specificity=0.37-1.00, area under the receiver operating characteristic curve=0.57-0.98) and a high risk of bias for most of the included studies.

conclusionsThe field of digital mental health tools is in its early stages, and high-quality evidence is lacking. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/25382.

Indexed as

diagnostic accuracydigital mental healthdigital questionnairepsychiatrysystematic review

Identifiers

PMID35353053
PMCPMC9008525

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.