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

Adult; Female; Humans; Male; Middle Aged; Socioeconomic Factors; Aged; Chronic Disease; *Computer Simulation; Longitudinal Studies; Comorbidity; *Health Status; Artificial Intelligence; cluster analysis; Life Change Events; primary care; Artificial Intelligence; case-based modelling; comorbid depression and physical health; complexity theory; differential equations; longitudinal analysis; nonlinear dynamics; Systems Analysis; Adult Survivors of Child Abuse/statistics & numerical data; Depression/*epidemiology/*physiopathology; Health Services Research/*methods; Intimate Partner Violence/statistics & numerical data; Primary Health Care/organization & administration

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).

Pages

1293-1309

Issue

6

Volume

24

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 December 5, 2021, https://neomed.omeka.net/items/show/6302.

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