Evidence map›Paper›PMID 37732500›Full record

ReviewDeutsches Arzteblatt international2023

Digital Health Applications in the Area of Mental Health.

Stefanie Schreiter, Lea Mascarell-Maricic, Orestis Rakitzis, Constantin Volkmann, Jakob Kaminski, Martin André Daniels

Abstract readReview
In one paragraph

Review in Deutsches Arzteblatt international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
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  3. Review
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  5. Article
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  9. Review
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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.

Stefanie SchreiterDepartment of Psychiatry and Neurosciences, CCM, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lea Mascarell-Maricic
Orestis Rakitzis
Constantin Volkmann
Jakob Kaminski
Martin André Daniels

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe introduction of digital health applications (DiGA) is a fundamental innovation in Germany. In the field of mental health, numerous applications are already available whose efficacy has been tested in clinical trials. We investigated whether, and to what extent, the use of DiGA can be recommended on the basis of the available evidence.

methodsIn this scoping review, we summarize the evidence supporting the use of DiGA in the mental health field through an examination of relevant publications that were retrieved by a systematic literature search. We provide an annotated tabular listing and discuss the current advantages of, and obstacles to, the care of mentally ill patients with the aid of DiGA.

resultsWe identified 17 DiGA for use in depression, anxiety disorders, addiction disorders, sleep disorders, stress/burnout, vaginismus, and chronic pain. These DiGA have been evaluated to date in 3 meta-analyses, 39 randomized controlled trials (RCTs), and two single-armed intervention trials. 23 of the 36 published trials were carried out with the direct participation of the manufacturers. 29 of the 39 RCTs were not blinded or contained no information regarding blinding. Active controls were used in 6 of the 39 RCTs. The reported effect sizes, with the exclusion of pre-post analyses, ranged from 0.16 to 1.79.

conclusionMost of the published studies display a high risk of bias, both because of the manufacturers' participation and because of methodological deficiencies. DiGA are an increasingly important therapeutic modality in psychiatry. The available evidence indicates that treatment effects are indeed present, but prospective comparisons with established treatments are still entirely lacking.

Indexed as

Digital HealthMental HealthAnxiety DisordersFemaleGermanyHumans

Identifiers

PMID37732500
PMCPMC10777310

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.