Evidence map›Paper›PMID 39995813›Full record

ArticleSchizophrenia research. Cognition2025

Designing smartphone-based cognitive assessments for schizophrenia: Perspectives from a multisite study.

Aishwarya Raje, Abhijit R Rozatkar, Urvakhsh Meherwan Mehta, Ritu Shrivastava, Ameya Bondre, Manaal Amir Ahmad, Anshika Malviya, Yogendra Sen, Deepak Tugnawat, Anant Bhan and 8 more

Abstract read
In one paragraph

Article in Schizophrenia research. Cognition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

18 authors.

Aishwarya RajeAll India Institute of Medical Sciences, Bhopal, India.
Abhijit R RozatkarAll India Institute of Medical Sciences, Bhopal, India.
Urvakhsh Meherwan MehtaNational Institute of Mental Health and Neurosciences, Bengaluru, India.
Ritu ShrivastavaSangath, Bhopal, India.
Ameya BondreSangath, Bhopal, India.
Manaal Amir AhmadSangath, Bhopal, India.
Anshika MalviyaSangath, Bhopal, India.
Yogendra SenSangath, Bhopal, India.
Deepak TugnawatSangath, Bhopal, India.
Anant BhanSangath, Bhopal, India.
Tamonud ModakAll India Institute of Medical Sciences, Bhopal, India.
Nabagata DasNational Institute of Mental Health and Neurosciences, Bengaluru, India.
Srilakshmi NagendraNational Institute of Mental Health and Neurosciences, Bengaluru, India.
Erlend LaneBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA.
Juan CastilloBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA.
John A NaslundDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, USA.
John TorousBeth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA.
Soumya ChoudharyNational Institute of Mental Health and Neurosciences, Bengaluru, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cognitive deficits represent a core symptom of schizophrenia and a principal contributor to illness disability, yet evaluating cognition in routine clinical settings is often not feasible as cognitive assessments take longer than a standard doctor's visit. Using smartphones to assess cognition in schizophrenia offers the advantages of convenience in that patients can complete assessments outside of the clinic, temporality in that longitudinal trends can be identified, and contextuality in that cognitive scores can be interpreted with other measures captured by the phone (e.g. sleep). The current study aims to design a battery of cognitive assessments corresponding to the MATRICs Consensus Battery of Cognition (MCCB), in partnership with people living with schizophrenia. Methodology: Focus group discussions (FGDs) and interviews were conducted with people diagnosed with schizophrenia across three sites (Boston, Bhopal, and Bangalore) to help design, refine, and assess the proposed smartphone battery of cognitive tests on the mindLAMP app. Interviews were conducted between December 2023 and March 2024. Inductive thematic analysis was used to analyze data. Results: Participants found the app and its proposed cognitive assessments to be acceptable, helpful, and easy to use. They particularly found the gamified nature of the cognitive tests to be appealing and engaging. However, they also proposed ways to further increase engagement by including more information about each cognitive test, more visual instructions, and more information about scoring. Across all sites, there were many similarities in themes. Discussion & conclusion: People living with schizophrenia, from different sites in the US and India, appear interested in using smartphone apps to track their cognition. Thematic analysis reinforces the importance of feedback and data sharing, although this presents a challenge, given the novel nature of smartphone-based cognitive measures that have not yet been standardized or validated.

Indexed as

CognitionDigital phenotypingDigital technologySchizophrenia

Identifiers

PMID39995813
PMCPMC11848491

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Registered trials

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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.