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Web-Based Graphic Representation of the Life Course of Mental Health: Cross-Sectional Study Across the Spectrum of Mood, Anxiety, Eating, and Substance Use Disorders.

Authors :
Aupperle RL
Paulus MP
Kuplicki R
Touthang J
Victor T
Yeh HW
Khalsa SS
Source :
JMIR mental health [JMIR Ment Health] 2020 Jan 28; Vol. 7 (1), pp. e16919. Date of Electronic Publication: 2020 Jan 28.
Publication Year :
2020

Abstract

Background: Although patient history is essential for informing mental health assessment, diagnosis, and prognosis, there is a dearth of standardized instruments measuring time-dependent factors relevant to psychiatric disorders. Previous research has demonstrated the potential utility of graphical representations, termed life charts, for depicting the complexity of the course of mental illness. However, the implementation of these assessments is limited by the exclusive focus on specific mental illnesses (ie, bipolar disorder) and the lack of intuitive graphical interfaces for data collection and visualization.<br />Objective: This study aimed to develop and test the utility of the Tulsa Life Chart (TLC) as a Web-based, structured approach for obtaining and graphically representing historical information on psychosocial and mental health events relevant across a spectrum of psychiatric disorders.<br />Methods: The TLC interview was completed at baseline by 499 participants of the Tulsa 1000, a longitudinal study of individuals with depressive, anxiety, substance use, or eating disorders and healthy comparisons (HCs). All data were entered electronically, and a 1-page electronic and interactive graphical representation was developed using the Google Visualization Application Programming Interface. For 8 distinct life epochs (periods of approximately 5-10 years), the TLC assessed the following factors: school attendance, hobbies, jobs, social support, substance use, mental health treatment, family structure changes, negative and positive events, and epoch and event-related mood ratings. We used generalized linear mixed models (GLMMs) to evaluate trajectories of each domain over time and by sex, age, and diagnosis, using case examples and Web-based interactive graphs to visualize data.<br />Results: GLMM analyses revealed main or interaction effects of epoch and diagnosis for all domains. Epoch by diagnosis interactions were identified for mood ratings and the number of negative-versus-positive events (all P values <.001), with all psychiatric groups reporting worse mood and greater negative-versus-positive events than HCs. These differences were most robust at different epochs, depending on diagnosis. There were also diagnosis and epoch main effects for substance use, mental health treatment received, social support, and hobbies (P<.001). User experience ratings (each on a 1-5 scale) revealed that participants found the TLC pleasant to complete (mean 3.07, SD 1.26) and useful for understanding their mental health (mean 3.07, SD 1.26), and that they were likely to recommend it to others (mean 3.42, SD 0.85).<br />Conclusions: The TLC provides a structured, Web-based transdiagnostic assessment of psychosocial history relevant for the diagnosis and treatment of psychiatric disorders. Interactive, 1-page graphical representations of the TLC allow for the efficient communication of historical life information that would be useful for clinicians, patients, and family members.<br /> (©Robin Leora Aupperle, Martin P Paulus, Rayus Kuplicki, James Touthang, Teresa Victor, Hung-Wen Yeh, Tulsa 1000 Investigators Tulsa 1000 Investigators, Sahib S Khalsa. Originally published in JMIR Mental Health (http://mental.jmir.org), 28.01.2020.)

Details

Language :
English
ISSN :
2368-7959
Volume :
7
Issue :
1
Database :
MEDLINE
Journal :
JMIR mental health
Publication Type :
Academic Journal
Accession number :
32012081
Full Text :
https://doi.org/10.2196/16919