Evidence map›Paper›PMID 41490575›Full record

ArticleJMIR research protocols2026

Evidence for Digital Mental Health Assessment Tools in the Post-COVID-19 Era: Protocol for a Systematic Review on Diagnostic Accuracy Across Age Groups.

Kathryn Babbitt, Erin Lucy Funnell, Nayra Martin-Key, Eleanor Barker, Sabine Bahn

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Kathryn BabbittCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, United Kingdom, 44 1223334151.ORCID 0009-0002-7197-3961
Erin Lucy FunnellCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, United Kingdom, 44 1223334151.ORCID 0000-0002-7652-8528
Nayra Martin-KeyCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, United Kingdom, 44 1223334151.ORCID 0000-0002-9731-3809
Eleanor BarkerEngineering Library, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-5472-2496
Sabine BahnCambridge Centre for Neuropsychiatric Research, Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge, CB3 0AS, United Kingdom, 44 1223334151.ORCID 0000-0003-4690-6302

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital assessment tools in health care are increasingly used to aid clinicians in diagnosing mental health conditions. Particularly since the quarantine and isolation guidelines of the COVID-19 pandemic moved much of health care online, there has been an accelerated adoption of digital assessment tools. The diagnostic accuracy of digital mental health assessment tools for a range of psychiatric conditions has yet to be fully explored, especially for their use in populations of older adults and children. Objective: This systematic review aims to (1) summarize recent studies on digital self-report question-and-answer-based mental health assessment tools for use in all ages across a range of psychiatric conditions (eg, the type and number of questions, if available; reference tests; timing; and blinding procedures), (2) present their validity (ie, diagnostic accuracy), and (3) assess study quality and applicability. Methods: The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guided the development of this protocol. The protocol has been registered with PROSPERO. The searches were guided by the PICO (population, intervention, comparator, and outcome) framework. A systematic search was conducted of the following databases of literature published since 2021: MEDLINE, Embase, Cochrane Library, ASSIA, Web of Science Core Collection, CINAHL, and PsycINFO. Searches of clinical trial databases and hand searching of reference lists will be completed. Two authors have independently screened titles and abstracts of identified papers and selected studies according to eligibility criteria, resolving inconsistencies through discussion. Full texts were screened following the same process. The authors extracted data using the Covidence data extraction tool (Veritas Health Innovation Ltd; eg, sensitivity and specificity). Two authors will use the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool to assess risk of bias for each full-text inclusion. Results: Scoping for this review began in December 2024. Searches of databases were completed in January 2025. Full-text screening and identification of the relevant gray literature were completed by the end of August 2025, and the final review is expected to be completed by December 2025. Conclusions: The review aims to present the validity and quality of the diagnostic accuracy of digital mental health assessment tools across different ages (including children and older adults), particularly following the COVID-19 pandemic due to the exponential increase in development and use of such tools. This review will provide evidence for the wider deployment of digital mental health assessment tools across a wide age range. There will also be a discussion about future research for digital tools and avenues for policy around digital mental health assessments.

Indexed as

COVID-19Mental DisordersMental HealthAdolescentAdultAgedChildHumansPandemicsSARS-CoV-2Self ReportSystematic Reviews as TopicTelemedicinedepressiondigital assessment tooldigital mental healthgeneralized anxiety disordersystematic reviewvalidity

Identifiers

PMID41490575
PMCPMC12768427

What OpenQuestion holds

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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.