Evidence map›Paper›PMID 41246203›Full record

ArticleDigital health

Highly adaptable smartphone-based monitoring for patients with severe mental illness: Feasibility and usability study.

Felix Machleid, Anette Schönewald, Esther Quinlivan, Linda Kokwaro, Louisa Schröder-Frekes, Toni Muffel, Caspar Wiegmann, Jakob Kaminski

Abstract read
In one paragraph

Article in Digital health. 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. Article
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

8 authors.

Felix MachleidDepartment of Psychiatry and Neurosciences, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Germany.ORCID https://orcid.org/0000-0002-6597-4178
Anette SchönewaldDepartment of Psychiatry and Neurosciences, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Germany.
Esther QuinlivanDepartment of Psychiatry and Neurosciences, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Germany.
Linda KokwaroDepartment of Psychiatry and Neurosciences, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Germany.
Louisa Schröder-FrekesVivantes Klinikum am Urban, Berlin, Germany.
Toni MuffelRecovery Cat GmbH, Berlin, Germany.
Caspar WiegmannRecovery Cat GmbH, Berlin, Germany.
Jakob KaminskiDepartment of Psychiatry and Neurosciences, Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Germany.ORCID https://orcid.org/0000-0001-8155-3683

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Severe mental illness (SMI) requires continuous treatment. Smartphone-based monitoring enables real-time data collection and offers a way of complementing clinical workflows by creating a bridge between patients and providers. Since their needs often differ, collaborative and highly adaptable tools are warranted. The objective of this study was to evaluate the feasibility of the highly adaptable remote-measurement-based care intervention Methods: Forty-nine patients were recruited for the 90-day trial and were provided with Recovery Cat a smartphone app designed to collaboratively set up and monitor clinical symptoms and functional parameters. Data were collected through daily self-reports. Feasibility was assessed by the dropout rate and user engagement, while user-friendliness was evaluated by the System Usability Scale (SUS). Results: 29 participants completed the study. The majority were single, unemployed, diagnosed with an affective disorder, had prior psychiatric treatment, and were in continuous outpatient psychiatric care. EMA data were available for 26 participants. 84.61% ( Conclusion: The results suggest that highly adaptable smartphone-based monitoring is feasible for patients with SMI. High adherence rates and positive usability scores indicate that this approach holds promise for enhancing mental health care.

Indexed as

Digital mental healthecological momentary assessmentmHealthmobile health technologiesremote measurement-based care

Identifiers

PMID41246203
PMCPMC12615936

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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.