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- Title
Digital phenotyping correlates of mobile cognitive measures in schizophrenia: A multisite global mental health feasibility trial.
- Authors
Cohen, Asher; Joshi, Devayani; Bondre, Ameya; Chand, Prabhat Kumar; Chaturvedi, Nirmal; Choudhary, Soumya; Dutt, Siddharth; Khan, Azaz; Langholm, Carsten; Kumar, Mohit; Gupta, Snehil; Nagendra, Srilakshmi; Reddy, Preethi V.; Rozatkar, Abhijit; Sen, Yogendra; Shrivastava, Ritu; Singh, Rahul; Thirthalli, Jagadisha; Tugnawat, Deepak Kumar; Bhan, Anant
- Abstract
Traditional cognitive assessments in schizophrenia are time-consuming and necessitate specialized training, making routine evaluation challenging. To overcome these limitations, this study investigates the feasibility and advantages of utilizing smartphone-based assessments to capture both cognitive functioning and digital phenotyping data and compare these results to gold standard measures. We conducted a secondary analysis of data from 76 individuals with schizophrenia, who were recruited across three sites (one in Boston, two in India) was conducted. The open-source mindLAMP smartphone app captured digital phenotyping data and Trails A/B assessments of attention / memory for up to 12 months. The smartphone-cognitive tasks exhibited potential for normal distribution and these scores showed small but significant correlations with the results from the Brief Assessment of Cognition in Schizophrenia, especially the digital span and symbol coding tasks (r2 = 0.21). A small but significant correlation (r2 = 0.29) between smartphone-derived cognitive scores and health-related behaviors such as sleep duration patterns was observed. Smartphone-based cognitive assessments show promise as cross-cultural tools that can capture relevant data on momentary states among individuals with schizophrenia. Cognitive results related to sleep suggest functional applications to digital phenotyping data, and the potential of this multimodal data approach in research. Author summary: While cognition is a well-known driver of functional disability in illnesses like schizophrenia, assessing cognition in routine clinical care is challenging because current assessments require expert training and can require at least half an hour to complete. Likewise, factors that we know impact cognition like sleep are also challenging to assess and so rarely integrated or discussed in care settings. In this pilot study, we explored how smartphones may help overcome both these challenges by enabling personalized and real-time data on cognition and sleep. This study recruited 76 people with schizophrenia at sites in the United States and India and asked them to use the open-source mindLAMP app to facilitate data capture of cognition through completing app-based exercises and sleep by allowing the collection of phone-based sensors (accelerometer and screen-state). Results showed that this smartphone data collection was feasible across these global study sites and that there was a correlation between sleep and cognition, suggesting potential for using this method to help guide better understanding and care in schizophrenia.
- Subjects
UNITED States; INDIA; PEARSON correlation (Statistics); MENTAL health; SECONDARY analysis; SMARTPHONES; TASK performance; DIGITAL health; SCHIZOPHRENIA; DESCRIPTIVE statistics; PHENOTYPES; COGNITION
- Publication
PLoS Digital Health, 2024, Vol 3, Issue 6, p1
- ISSN
2767-3170
- Publication type
Article
- DOI
10.1371/journal.pdig.0000526