Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Observational Study
. 2018 Jan 24;8(1):e016620.
doi: 10.1136/bmjopen-2017-016620.

Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample

Affiliations
Observational Study

Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample

Teresa A Victor et al. BMJ Open. .

Abstract

Introduction: Although neuroscience has made tremendous progress towards understanding the basic neural circuitry underlying important processes such as attention, memory and emotion, little progress has been made in applying these insights to psychiatric populations to make clinically meaningful treatment predictions. The overall aim of the Tulsa 1000 (T-1000) study is to use the NIMH Research Domain Criteria framework in order to establish a robust and reliable dimensional set of variables that quantifies the positive and negative valence, cognition and arousal domains, including interoception, to generate clinically useful treatment predictions.

Methods and analysis: The T-1000 is a naturalistic study that will recruit, assess and longitudinally follow 1000 participants, including healthy controls and treatment-seeking individuals with mood, anxiety, substance use and eating disorders. Each participant will undergo interview, behavioural, biomarker and neuroimaging assessments over the course of 1 year. The study goal is to determine how disorders of affect, substance use and eating behaviour organise across different levels of analysis (molecules, genes, cells, neural circuits, physiology, behaviour and self-report) to predict symptom severity, treatment outcome and long-term prognosis. The data will be used to generate computational models based on Bayesian statistics. The final end point of this multilevel latent variable analysis will be standardised assessments that can be developed into clinical tools to help clinicians predict outcomes and select the best intervention for each individual, thereby reducing the burden of mental disorders, and taking psychiatry a step closer towards personalised medicine.

Ethics and dissemination: Ethical approval was obtained from Western Institutional Review Board screening protocol #20101611. The dissemination plan includes informing health professionals of results for clinical practice, submitting results to journals for peer-reviewed publication, presenting results at national and international conferences and making the dataset available to researchers and mental health professionals.

Trial registration number: NCT02450240; Pre-results.

Keywords: adult psychiatry; anxiety disorders; eating disorders; magnetic resonance imaging; mental health.

PubMed Disclaimer

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Tulsa 1000 workflow schematic. BOLD, blood oxygen level-dependent; DAST, drug abuse screening test; DTI, diffusion tensor imaging; EEG, electroencephalogram; MINI, Mini International Neuropsychiatric Interview; OASIS, Overall Anxiety Severity and Impairment Scale; PHQ-9, Patient Health Questionnaire; PROMIS, Patient-Reported Outcome Measurement Information System; SCOFF, Sick, Control, One, Fat, Food Questionnaire; T1/T2, T1-weighted (longitudinal relaxation time) and T2-weighted (transverse relaxation time).

References

    1. Moussavi S, Chatterji S, Verdes E, et al. . Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 2007;370:851–8. 10.1016/S0140-6736(07)61415-9 - DOI - PubMed
    1. Kessler RC, Ruscio AM, Shear K, et al. . Epidemiology of anxiety disorders. Curr Top Behav Neurosci 2010;2:21–35. - PubMed
    1. Whiteford HA, Degenhardt L, Rehm J, et al. . Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet 2013;382:1575–86. 10.1016/S0140-6736(13)61611-6 - DOI - PubMed
    1. Kessler RC, Petukhova M, Sampson NA, et al. . Twelve-month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. Int J Methods Psychiatr Res 2012;21:169–84. 10.1002/mpr.1359 - DOI - PMC - PubMed
    1. Roy-Byrne PP, Davidson KW, Kessler RC, et al. . Anxiety disorders and comorbid medical illness. Gen Hosp Psychiatry 2008;30:208–25. 10.1016/j.genhosppsych.2007.12.006 - DOI - PubMed

Publication types

Associated data