New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research.

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Abstract

A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data.

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Understanding individual human mobility patterns

M. González, A L Barabási, C. Hidalgo (2008)

Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six month period. We find that in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic length scale and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent based modeling.

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Schizophrenia: a concise overview of incidence, prevalence, and mortality.

J. McGrath, S. Saha, D. CHANT … (2008)

Recent systematic reviews have encouraged the psychiatric research community to reevaluate the contours of schizophrenia epidemiology. This paper provides a concise overview of three related systematic reviews on the incidence, prevalence, and mortality associated with schizophrenia. The reviews shared key methodological features regarding search strategies, analysis of the distribution of the frequency estimates, and exploration of the influence of key variables (sex, migrant status, urbanicity, secular trend, economic status, and latitude). Contrary to previous interpretations, the incidence of schizophrenia shows prominent variation between sites. The median incidence of schizophrenia was 15.2/100,000 persons, and the central 80% of estimates varied over a fivefold range (7.7-43.0/100,000). The rate ratio for males:females was 1.4:1. Prevalence estimates also show prominent variation. The median lifetime morbid risk for schizophrenia was 7.2/1,000 persons. On the basis of the standardized mortality ratio, people with schizophrenia have a two- to threefold increased risk of dying (median standardized mortality ratio = 2.6 for all-cause mortality), and this differential gap in mortality has increased over recent decades. Compared with native-born individuals, migrants have an increased incidence and prevalence of schizophrenia. Exposures related to urbanicity, economic status, and latitude are also associated with various frequency measures. In conclusion, the epidemiology of schizophrenia is characterized by prominent variability and gradients that can help guide future research.

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Ecological momentary assessment.

Saul Shiffman, Arthur Stone, Michael R. Hufford (2008)

Assessment in clinical psychology typically relies on global retrospective self-reports collected at research or clinic visits, which are limited by recall bias and are not well suited to address how behavior changes over time and across contexts. Ecological momentary assessment (EMA) involves repeated sampling of subjects' current behaviors and experiences in real time, in subjects' natural environments. EMA aims to minimize recall bias, maximize ecological validity, and allow study of microprocesses that influence behavior in real-world contexts. EMA studies assess particular events in subjects' lives or assess subjects at periodic intervals, often by random time sampling, using technologies ranging from written diaries and telephones to electronic diaries and physiological sensors. We discuss the rationale for EMA, EMA designs, methodological and practical issues, and comparisons of EMA and recall data. EMA holds unique promise to advance the science and practice of clinical psychology by shedding light on the dynamics of behavior in real-world settings.