Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data

Abstract BackgroundIndia has the world’s largest number of suicides, but there is little research on the trends in suicidal thoughts, especially for individuals with psychosis. More research is necessary to develop preventive interventions. Smartphone-based ecological momentar...

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Main Authors: Ameya P Bondre, Aashish Ranjan, Ritu Shrivastava, Deepak Tugnawat, Nirmal Kumar Chaturvedi, Anant Bhan, Snehil Gupta, Abhijit R Rozatkar, Srilakshmi Nagendra, Siddharth Dutt, Soumya Choudhary, Preethi V Reddy, Urvakhsh Meherwan Mehta, John A Naslund, John Torous
Format: Article
Language:English
Published: JMIR Publications 2025-05-01
Series:JMIR Formative Research
Online Access:https://formative.jmir.org/2025/1/e67745
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author Ameya P Bondre
Aashish Ranjan
Ritu Shrivastava
Deepak Tugnawat
Nirmal Kumar Chaturvedi
Anant Bhan
Snehil Gupta
Abhijit R Rozatkar
Srilakshmi Nagendra
Siddharth Dutt
Soumya Choudhary
Preethi V Reddy
Urvakhsh Meherwan Mehta
John A Naslund
John Torous
author_facet Ameya P Bondre
Aashish Ranjan
Ritu Shrivastava
Deepak Tugnawat
Nirmal Kumar Chaturvedi
Anant Bhan
Snehil Gupta
Abhijit R Rozatkar
Srilakshmi Nagendra
Siddharth Dutt
Soumya Choudhary
Preethi V Reddy
Urvakhsh Meherwan Mehta
John A Naslund
John Torous
author_sort Ameya P Bondre
collection DOAJ
description Abstract BackgroundIndia has the world’s largest number of suicides, but there is little research on the trends in suicidal thoughts, especially for individuals with psychosis. More research is necessary to develop preventive interventions. Smartphone-based ecological momentary assessments (EMAs) can assess dynamic symptoms, but most EMA studies are conducted in higher income settings and have shorter (≤1 month) follow-up periods. ObjectiveThis study aimed to examine the duration of onset to offset of suicidal ideation (SI) in tertiary hospital outpatients with psychosis in India. MethodsThis study is an exploratory, secondary analysis of smartphone EMA data nested within the ongoing “Smartphone Health Assessment for Relapse Prevention (SHARP)” project. Tertiary hospital outpatients (n=50) with early course schizophrenia at 2 socioculturally different sites in India were recruited and given the “mindLAMP” app for monitoring mood through daily EMA surveys. The mood survey matched the 9-item Patient Health Questionnaire; the ninth item was used to define an instance of SI (score ≥1). A total of 14 patients with ≥1 SI instances who met the site-specific EMA survey use cutoff were included. We examined the between- and within-person variability in SI and computed the timescale of “episodic” SI (sequences of consecutive daily observations of SI score ≥1). Positive and Negative Syndrome Scale (PANSS) was used to assess changes in psychosis symptoms and its relationship with the temporality of SI. ResultsOver approximately 11 (SD 2.1) months of EMA reporting on average, 3253 mood surveys were filled by the 14 participants (median 213, IQR 147‐256). A total of 521 instances of SI were reported. Monthly SI instances showed substantial within- and between-person variations. Timescale summary statistics revealed episodic SI patterns in 11 patients, with an average of 5.9 episodes (SD 4.4; range:1‐14; n=65) with an episode lasting on average 2.5 days (SD 1.5; range:1‐5.3; n=27). There was an average lag of approximately 59, 66, and 81 days between the time of the first drop in PANSS positive, negative, and general psychopathology scores, respectively, and the last reported SI instance. Results after imputation of missing data showed an average of 12.1 episodes and 228 days (average lag) between the first drop in PANSS scores and last reported SI. This indicated that SI was an enduring vulnerability subsequent to the beginning of clinical improvement in psychosis. ConclusionsOur study adds to the much-needed evidence base in India to measure the dynamics of suicidal thinking within an individual, for more targeted preventive interventions. Further steps in EMA research are highlighted such as the use of higher frequency “burst” surveys to assess the duration of an SI episode in hours or minutes, and inclusion of both active and passive SI markers to measure the timescale of suicidal thinking.
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spelling doaj-art-79b1b7c9c59d4503a2d4e1de2879d3402025-08-20T02:03:17ZengJMIR PublicationsJMIR Formative Research2561-326X2025-05-019e67745e6774510.2196/67745Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment DataAmeya P Bondrehttp://orcid.org/0000-0003-1359-4613Aashish Ranjanhttp://orcid.org/0009-0004-5813-5394Ritu Shrivastavahttp://orcid.org/0000-0002-1139-0337Deepak Tugnawathttp://orcid.org/0000-0003-4978-9981Nirmal Kumar Chaturvedihttp://orcid.org/0009-0004-5978-5428Anant Bhanhttp://orcid.org/0000-0002-7456-535XSnehil Guptahttp://orcid.org/0000-0001-5498-2917Abhijit R Rozatkarhttp://orcid.org/0000-0002-8392-1395Srilakshmi Nagendrahttp://orcid.org/0000-0003-2855-5270Siddharth Dutthttp://orcid.org/0000-0001-8981-6986Soumya Choudharyhttp://orcid.org/0000-0002-7522-6923Preethi V Reddyhttp://orcid.org/0000-0002-7229-1869Urvakhsh Meherwan Mehtahttp://orcid.org/0000-0002-2252-9189John A Naslundhttp://orcid.org/0000-0001-6777-0104John Toroushttp://orcid.org/0000-0002-5362-7937 Abstract BackgroundIndia has the world’s largest number of suicides, but there is little research on the trends in suicidal thoughts, especially for individuals with psychosis. More research is necessary to develop preventive interventions. Smartphone-based ecological momentary assessments (EMAs) can assess dynamic symptoms, but most EMA studies are conducted in higher income settings and have shorter (≤1 month) follow-up periods. ObjectiveThis study aimed to examine the duration of onset to offset of suicidal ideation (SI) in tertiary hospital outpatients with psychosis in India. MethodsThis study is an exploratory, secondary analysis of smartphone EMA data nested within the ongoing “Smartphone Health Assessment for Relapse Prevention (SHARP)” project. Tertiary hospital outpatients (n=50) with early course schizophrenia at 2 socioculturally different sites in India were recruited and given the “mindLAMP” app for monitoring mood through daily EMA surveys. The mood survey matched the 9-item Patient Health Questionnaire; the ninth item was used to define an instance of SI (score ≥1). A total of 14 patients with ≥1 SI instances who met the site-specific EMA survey use cutoff were included. We examined the between- and within-person variability in SI and computed the timescale of “episodic” SI (sequences of consecutive daily observations of SI score ≥1). Positive and Negative Syndrome Scale (PANSS) was used to assess changes in psychosis symptoms and its relationship with the temporality of SI. ResultsOver approximately 11 (SD 2.1) months of EMA reporting on average, 3253 mood surveys were filled by the 14 participants (median 213, IQR 147‐256). A total of 521 instances of SI were reported. Monthly SI instances showed substantial within- and between-person variations. Timescale summary statistics revealed episodic SI patterns in 11 patients, with an average of 5.9 episodes (SD 4.4; range:1‐14; n=65) with an episode lasting on average 2.5 days (SD 1.5; range:1‐5.3; n=27). There was an average lag of approximately 59, 66, and 81 days between the time of the first drop in PANSS positive, negative, and general psychopathology scores, respectively, and the last reported SI instance. Results after imputation of missing data showed an average of 12.1 episodes and 228 days (average lag) between the first drop in PANSS scores and last reported SI. This indicated that SI was an enduring vulnerability subsequent to the beginning of clinical improvement in psychosis. ConclusionsOur study adds to the much-needed evidence base in India to measure the dynamics of suicidal thinking within an individual, for more targeted preventive interventions. Further steps in EMA research are highlighted such as the use of higher frequency “burst” surveys to assess the duration of an SI episode in hours or minutes, and inclusion of both active and passive SI markers to measure the timescale of suicidal thinking.https://formative.jmir.org/2025/1/e67745
spellingShingle Ameya P Bondre
Aashish Ranjan
Ritu Shrivastava
Deepak Tugnawat
Nirmal Kumar Chaturvedi
Anant Bhan
Snehil Gupta
Abhijit R Rozatkar
Srilakshmi Nagendra
Siddharth Dutt
Soumya Choudhary
Preethi V Reddy
Urvakhsh Meherwan Mehta
John A Naslund
John Torous
Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
JMIR Formative Research
title Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
title_full Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
title_fullStr Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
title_full_unstemmed Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
title_short Analyzing Trends in Suicidal Thoughts Among Patients With Psychosis in India: Exploratory Secondary Analysis of Smartphone Ecological Momentary Assessment Data
title_sort analyzing trends in suicidal thoughts among patients with psychosis in india exploratory secondary analysis of smartphone ecological momentary assessment data
url https://formative.jmir.org/2025/1/e67745
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