Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach.
Title
Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach.
Creator
Castellani Brian; Griffiths Frances; Rajaram Rajeev; Gunn Jane
Publisher
Journal of evaluation in clinical practice
Date
2018
2018-12
Description
While comorbid depression/physical health is a major clinical concern, the conventional methods of medicine make it difficult to model the complexities of this relationship. Such challenges include cataloguing multiple trends, developing multiple complex aetiological explanations, and modelling the collective large-scale dynamics of these trends. Using a case-based complexity approach, this study engaged in a richly described case study to demonstrate the utility of computational modelling for primary care research. N = 259 people were subsampled from the Diamond database, one of the largest primary care depression cohort studies worldwide. A global measure of depressive symptoms (PHQ-9) and physical health (PCS-12) were assessed at 3, 6, 9, and 12 months and then annually for a total of 7 years. Eleven trajectories and 2 large-scale collective dynamics were identified, revealing that while depression is comorbid with poor physical health, chronic illness is often low dynamic and not always linked to depression. Also, some of the cases in the unhealthy and oscillator trends remain ill without much chance of improvement. Finally, childhood abuse, partner violence, and negative life events are greater amongst unhealthy trends. Computational modelling offers a major advance for health researchers to account for the diversity of primary care patients and for developing better prognostic models for team-based interdisciplinary care.
Subject
artificial intelligence; case-based modelling; Child Abuse; cluster analysis; comorbid depression and physical health; Comorbidity; complexity theory; Computer Simulation; Depression – Therapy; differential equations; Health Status; Human; Intimate Partner Violence; longitudinal analysis; Models; nonlinear dynamics; primary care; Primary Health Care; Prospective Studies; Questionnaires; Research Personnel; Scales; Theoretical
Identifier
Rights
Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).
Citation
Castellani Brian; Griffiths Frances; Rajaram Rajeev; Gunn Jane, “Exploring comorbid depression and physical health trajectories: A case-based computational modelling approach.,” NEOMED Bibliography Database, accessed October 12, 2024, https://neomed.omeka.net/items/show/4492.