Cargando…
Outcome measurement in mental health services: insights from symptom networks
BACKGROUND: In mental health, outcomes are currently measured by changes of individual scores. However, such an analysis on individual scores does not take into account the interaction between symptoms, which could yield crucial information while investigating outcomes. Network analysis techniques c...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599349/ https://www.ncbi.nlm.nih.gov/pubmed/31253106 http://dx.doi.org/10.1186/s12888-019-2175-7 |
_version_ | 1783430946356199424 |
---|---|
author | Barbalat, Guillaume van den Bergh, Don Kossakowski, Jolanda Jacqueline |
author_facet | Barbalat, Guillaume van den Bergh, Don Kossakowski, Jolanda Jacqueline |
author_sort | Barbalat, Guillaume |
collection | PubMed |
description | BACKGROUND: In mental health, outcomes are currently measured by changes of individual scores. However, such an analysis on individual scores does not take into account the interaction between symptoms, which could yield crucial information while investigating outcomes. Network analysis techniques can be used to routinely study these systems of interacting symptoms. The present study aimed at comparing outcomes using individual scores vs. symptom networks, after a 1 year intervention at a local community mental health centre. METHODS: We used the Health of the Nation Outcomes Scales, which defines a set of 12 scales investigating mental health and social functioning. We first assessed how individual scores varied from baseline to end point and which items were associated to treatment response. Second, using network analysis techniques, we measured the overall connectivity of the networks and determined the most important symptoms. RESULTS: The individual scores analysis revealed a significant improvement amongst most scales. No specific factors were related to treatment response at end point. At end point, network analysis revealed a very densely connected network while agitation and substance use were the most connected symptoms. CONCLUSIONS: Individual scores and symptom network analysis resulted in very different outcomes, with network analysis toning down positive results gained from individual scores analysis. The strong connectivity of patients’ network at end point may reflect their increased complexity. Allocating more resources to interventions tailored to symptoms that are the most connected would decrease network connectivity and improve patients’ prognosis. When investigating outcomes, network analysis could give insights complementary to standard analysis on individual scores. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12888-019-2175-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6599349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65993492019-07-11 Outcome measurement in mental health services: insights from symptom networks Barbalat, Guillaume van den Bergh, Don Kossakowski, Jolanda Jacqueline BMC Psychiatry Research Article BACKGROUND: In mental health, outcomes are currently measured by changes of individual scores. However, such an analysis on individual scores does not take into account the interaction between symptoms, which could yield crucial information while investigating outcomes. Network analysis techniques can be used to routinely study these systems of interacting symptoms. The present study aimed at comparing outcomes using individual scores vs. symptom networks, after a 1 year intervention at a local community mental health centre. METHODS: We used the Health of the Nation Outcomes Scales, which defines a set of 12 scales investigating mental health and social functioning. We first assessed how individual scores varied from baseline to end point and which items were associated to treatment response. Second, using network analysis techniques, we measured the overall connectivity of the networks and determined the most important symptoms. RESULTS: The individual scores analysis revealed a significant improvement amongst most scales. No specific factors were related to treatment response at end point. At end point, network analysis revealed a very densely connected network while agitation and substance use were the most connected symptoms. CONCLUSIONS: Individual scores and symptom network analysis resulted in very different outcomes, with network analysis toning down positive results gained from individual scores analysis. The strong connectivity of patients’ network at end point may reflect their increased complexity. Allocating more resources to interventions tailored to symptoms that are the most connected would decrease network connectivity and improve patients’ prognosis. When investigating outcomes, network analysis could give insights complementary to standard analysis on individual scores. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12888-019-2175-7) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-28 /pmc/articles/PMC6599349/ /pubmed/31253106 http://dx.doi.org/10.1186/s12888-019-2175-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Barbalat, Guillaume van den Bergh, Don Kossakowski, Jolanda Jacqueline Outcome measurement in mental health services: insights from symptom networks |
title | Outcome measurement in mental health services: insights from symptom networks |
title_full | Outcome measurement in mental health services: insights from symptom networks |
title_fullStr | Outcome measurement in mental health services: insights from symptom networks |
title_full_unstemmed | Outcome measurement in mental health services: insights from symptom networks |
title_short | Outcome measurement in mental health services: insights from symptom networks |
title_sort | outcome measurement in mental health services: insights from symptom networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599349/ https://www.ncbi.nlm.nih.gov/pubmed/31253106 http://dx.doi.org/10.1186/s12888-019-2175-7 |
work_keys_str_mv | AT barbalatguillaume outcomemeasurementinmentalhealthservicesinsightsfromsymptomnetworks AT vandenberghdon outcomemeasurementinmentalhealthservicesinsightsfromsymptomnetworks AT kossakowskijolandajacqueline outcomemeasurementinmentalhealthservicesinsightsfromsymptomnetworks |