Longitudinal symptom changes and association with home time in people with schizophrenia: An observational digital phenotyping study

Ranjan, Tanvi; Melcher, Jennifer R.; Keshavan, Matcheri S.; Smith, Maurice A.; Torous, John

doi:10.1016/j.schres.2022.02.031

Cited by 17 publications

(11 citation statements)

References 10 publications

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“…Even for less technical approaches that do not involve sensors, there are many cases where simple assessment tools, such as patient-reported outcomes, are reported differently when the same data are collected digitally vs. in person. For example, patient-reported scores for depression and anxiety are not always the same when assessed in different formats as some people may report more severe symptoms to an app vs in person 18 . Relatedly, standards for defining digital biomarkers are still under development (e.g., what constitutes a “step” from a step counter) and determining the validity of digital endpoints remains challenging.…”

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confidence: 99%

Regulatory considerations to keep pace with innovation in digital health products

2022

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Rapid innovation and proliferation of software as a medical device have accelerated the clinical use of digital technologies across a wide array of medical conditions. Current regulatory pathways were developed for traditional (hardware) medical devices and offer a useful structure, but the evolution of digital devices requires concomitant innovation in regulatory approaches to maximize the potential benefits of these emerging technologies. A number of specific adaptations could strengthen current regulatory oversight while promoting ongoing innovation.

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confidence: 99%

Regulatory considerations to keep pace with innovation in digital health products

2022

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“…However, we also nd that EMA psychosis was also negatively associated with mobility entropy, which may suggest psychotic symptoms are relieved by mobility within or near the home environment (Figure 5, Table 2). Hence, the nding from the 2022 study that psychosis was elevated at home may be confounded by the presence of different levels of mobility entropy for the study cohorts [27].…”

Section: Discussionmentioning

confidence: 99%

Towards Clinical Subtypes in Schizophrenia: Integrating Cognitive, Functional, and Digital Phenotyping Assessments

Byun,

Lane,

Langholm

et al. 2024

Preprint

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Heterogeneity in the clinical presentation of schizophrenia impairs both proper and preventative care. The digital phenotyping data gathered from an international multi-site cohort study in people with schizophrenia (SZ) offers a novel opportunity to explore clinically meaningful subtypes in the context of clinical, functional, and cognitive data. Using a set of behavioral features derived from smartphone digital phenotyping, clinical assessment of symptoms including PANSS, clinical assessment of cognition with BACS, and clinical assessment of functioning with the social functioning assessments over the target period of twelve months, we found that the international cohort of 74 patients were categorized into three well-defined clusters that suggest clinically actionable targets from differential correlations in each. Namely, the identified clusters seemed to share phenotypic traits with the affective psychosis with more severe symptomatic presentation, a non-affective SZ with functional impairment, and a higher functioning non-affective SZ cluster. Partial correlation analysis further highlighted the emergence of different features per cluster, where anxiety symptoms were most notable for one group, whereas psychotic symptoms were most notable for the other two. Importantly, we showcase an analysis pipeline that transparently addresses challenges of missing data and potential skew so that this research methodology can be applied to future prospective validation studies. This study hopes to build a foundation for future digital phenotyping clustering work by scaling up to new sites, and populations to uncover the nature and extent of heterogeneity in schizophrenia.

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“…While the studies differed in their clinical populations (patients with schizophrenia or depression/anxiety; college students with stress/anxiety), they all collected two common digital phenotyping data streams: geolocation (GPS) and accelerometer data. Each study presented participants with a symptom survey at least every 3 days 12–16. All participants in each study (including those who were discontinued for non-adherence to protocol) were included in this analysis.…”

Section: Methodsmentioning

confidence: 99%

Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies

Currey

Torous

2023

BMJ Ment Health

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BackgroundDigital phenotyping methods present a scalable tool to realise the potential of personalised medicine. But underlying this potential is the need for digital phenotyping data to represent accurate and precise health measurements.ObjectiveTo assess the impact of population, clinical, research and technological factors on the digital phenotyping data quality as measured by rates of missing digital phenotyping data.MethodsThis study analyses retrospective cohorts of mindLAMP smartphone application digital phenotyping studies run at Beth Israel Deaconess Medical Center between May 2019 and March 2022 involving 1178 participants (studies of college students, people with schizophrenia and people with depression/anxiety). With this large combined data set, we report on the impact of sampling frequency, active engagement with the application, phone type (Android vs Apple), gender and study protocol features on missingness/data quality.FindingsMissingness from sensors in digital phenotyping is related to active user engagement with the application. After 3 days of no engagement, there was a 19% decrease in average data coverage for both Global Positioning System and accelerometer. Data sets with high degrees of missingness can generate incorrect behavioural features that may lead to faulty clinical interpretations.ConclusionsDigital phenotyping data quality requires ongoing technical and protocol efforts to minimise missingness. Adding run-in periods, education with hands-on support and tools to easily monitor data coverage are all productive strategies studies can use today.Clinical implicationsWhile it is feasible to capture digital phenotyping data from diverse populations, clinicians should consider the degree of missingness in the data before using them for clinical decision-making.

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Longitudinal symptom changes and association with home time in people with schizophrenia: An observational digital phenotyping study

Cited by 17 publications

References 10 publications

Regulatory considerations to keep pace with innovation in digital health products

Regulatory considerations to keep pace with innovation in digital health products

Towards Clinical Subtypes in Schizophrenia: Integrating Cognitive, Functional, and Digital Phenotyping Assessments

Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies

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