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Graphical methods for understanding changes in states: Understanding medication use pathways
OBJECTIVES: As epidemiological studies become longer and larger, the field needs novel graphical methods to visualize complex longitudinal data. The aim of this study was to present the Slinkyplot, a longitudinal crosstabulation, to illustrate patterns of antidepressant use in a large prospective co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720228/ https://www.ncbi.nlm.nih.gov/pubmed/35894783 http://dx.doi.org/10.1002/mpr.1932 |
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author | Wise, Elizabeth A. Adams, Roy J. Lyketsos, Constantine G. Leoutsakos, Jeannie‐Marie |
author_facet | Wise, Elizabeth A. Adams, Roy J. Lyketsos, Constantine G. Leoutsakos, Jeannie‐Marie |
author_sort | Wise, Elizabeth A. |
collection | PubMed |
description | OBJECTIVES: As epidemiological studies become longer and larger, the field needs novel graphical methods to visualize complex longitudinal data. The aim of this study was to present the Slinkyplot, a longitudinal crosstabulation, to illustrate patterns of antidepressant use in a large prospective cohort of older adults with mild cognitive impairment. METHODS: Data from the National Alzheimer's Coordinating Center are used to track switches between different states and types of antidepressant use. A Slinkyplot is populated with rows representing the state of medication use at each timepoint and columns representing the state at each subsequent visit. RESULTS: The constructed Slinkyplots display the common practice of switching on and off different antidepressants over time, with citalopram, sertraline, and bupropion most commonly used followed by switching to another SSRI or SNRI as second‐line treatment. CONCLUSIONS: Slinkyplots are an innovative graphical means of visualizing complex patterns of transitions between different states over time for large longitudinal studies. |
format | Online Article Text |
id | pubmed-9720228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97202282022-12-06 Graphical methods for understanding changes in states: Understanding medication use pathways Wise, Elizabeth A. Adams, Roy J. Lyketsos, Constantine G. Leoutsakos, Jeannie‐Marie Int J Methods Psychiatr Res Original Articles OBJECTIVES: As epidemiological studies become longer and larger, the field needs novel graphical methods to visualize complex longitudinal data. The aim of this study was to present the Slinkyplot, a longitudinal crosstabulation, to illustrate patterns of antidepressant use in a large prospective cohort of older adults with mild cognitive impairment. METHODS: Data from the National Alzheimer's Coordinating Center are used to track switches between different states and types of antidepressant use. A Slinkyplot is populated with rows representing the state of medication use at each timepoint and columns representing the state at each subsequent visit. RESULTS: The constructed Slinkyplots display the common practice of switching on and off different antidepressants over time, with citalopram, sertraline, and bupropion most commonly used followed by switching to another SSRI or SNRI as second‐line treatment. CONCLUSIONS: Slinkyplots are an innovative graphical means of visualizing complex patterns of transitions between different states over time for large longitudinal studies. John Wiley and Sons Inc. 2022-07-27 /pmc/articles/PMC9720228/ /pubmed/35894783 http://dx.doi.org/10.1002/mpr.1932 Text en © 2022 The Authors. International Journal of Methods in Psychiatric Research published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Articles Wise, Elizabeth A. Adams, Roy J. Lyketsos, Constantine G. Leoutsakos, Jeannie‐Marie Graphical methods for understanding changes in states: Understanding medication use pathways |
title | Graphical methods for understanding changes in states: Understanding medication use pathways |
title_full | Graphical methods for understanding changes in states: Understanding medication use pathways |
title_fullStr | Graphical methods for understanding changes in states: Understanding medication use pathways |
title_full_unstemmed | Graphical methods for understanding changes in states: Understanding medication use pathways |
title_short | Graphical methods for understanding changes in states: Understanding medication use pathways |
title_sort | graphical methods for understanding changes in states: understanding medication use pathways |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720228/ https://www.ncbi.nlm.nih.gov/pubmed/35894783 http://dx.doi.org/10.1002/mpr.1932 |
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