TY - JOUR
T1 - Network structure of time-varying depressive symptoms through dynamic time warp analysis in late-life depression
AU - van Zelst, Denise C. R.
AU - Veltman, Eveline M.
AU - Rhebergen, Didi
AU - Naarding, Paul
AU - Kok, Almar A. L.
AU - Ottenheim, Nathaly Rius
AU - Giltay, Erik J.
N1 - Funding Information: The infrastructure for the NESDO study ( https://nesdo.onderzoek.io/ ) is funded through the Fonds NutsOhra [project0701‐065]; Stichting tot Steun VCVGZ, NARSAD The Brain and Behaviour Research Fund [grant ID 41080]; and the participating universities and mental health care organizations (VU University Medical Centre, Leiden University Medical Centre, University Medical Centre Groningen, UMC St Radboud, GGZ inGeest, GGNet, GGZ Nijmegen, GGZ Rivierduinen, Lentis, and Parnassia). This research received no specific grant from any funding agency, commercial or not‐for‐profit sectors. Funding Information: The infrastructure for the NESDO study (https://nesdo.onderzoek.io/) is funded through the Fonds NutsOhra [project0701-065]; Stichting tot Steun VCVGZ, NARSAD The Brain and Behaviour Research Fund [grant ID 41080]; and the participating universities and mental health care organizations (VU University Medical Centre, Leiden University Medical Centre, University Medical Centre Groningen, UMC St Radboud, GGZ inGeest, GGNet, GGZ Nijmegen, GGZ Rivierduinen, Lentis, and Parnassia). This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Publisher Copyright: © 2022 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - OBJECTIVES: Late-life major depressive disorder (MDD) can be conceptualized as a complex dynamic system. However, it is not straightforward how to analyze the covarying depressive symptoms over time in case of sparse panel data. Dynamic time warping (DTW) analysis may yield symptom networks and dimensions both at the patient and group level. METHODS: In the Netherlands Study of Depression in Older People (NESDO) depressive symptoms were assessed every 6 months using the 30-item Inventory of Depressive Symptomatology (IDS) with up to 13 assessments per participant. Our sample consisted of 182 persons, aged ≥ 60 years, with an IDS total score of 26 or higher at baseline. Symptom networks dimensions, and centrality metrics were analyzed using DTW and Distatis analyses. RESULTS: The mean age was 69.8 years (SD 7.1), with 69.0% females, and a mean IDS score of 38.0 (SD = 8.7). DTW enabled visualization of an idiographic symptom network in a single NESDO participant. In the group-level nomothetic approach, four depressive symptom dimensions were identified: "core symptoms", "lethargy/somatic", "sleep", and "appetite/atypical". Items of the "internalizing symptoms" dimension had the highest centrality, whose symptom changes over time were most similar to those changes of other symptoms. CONCLUSIONS: DTW revealed symptom networks and dimensions based on the within-person symptom changes in older MDD patients. Its centrality metrics signal the most influential symptoms, which may aid personalized care.
AB - OBJECTIVES: Late-life major depressive disorder (MDD) can be conceptualized as a complex dynamic system. However, it is not straightforward how to analyze the covarying depressive symptoms over time in case of sparse panel data. Dynamic time warping (DTW) analysis may yield symptom networks and dimensions both at the patient and group level. METHODS: In the Netherlands Study of Depression in Older People (NESDO) depressive symptoms were assessed every 6 months using the 30-item Inventory of Depressive Symptomatology (IDS) with up to 13 assessments per participant. Our sample consisted of 182 persons, aged ≥ 60 years, with an IDS total score of 26 or higher at baseline. Symptom networks dimensions, and centrality metrics were analyzed using DTW and Distatis analyses. RESULTS: The mean age was 69.8 years (SD 7.1), with 69.0% females, and a mean IDS score of 38.0 (SD = 8.7). DTW enabled visualization of an idiographic symptom network in a single NESDO participant. In the group-level nomothetic approach, four depressive symptom dimensions were identified: "core symptoms", "lethargy/somatic", "sleep", and "appetite/atypical". Items of the "internalizing symptoms" dimension had the highest centrality, whose symptom changes over time were most similar to those changes of other symptoms. CONCLUSIONS: DTW revealed symptom networks and dimensions based on the within-person symptom changes in older MDD patients. Its centrality metrics signal the most influential symptoms, which may aid personalized care.
KW - Inventory of Depressive Symptomatology
KW - cluster analysis
KW - dynamic time warp analysis
KW - late-life depression
KW - major depressive disorder
KW - network analysis
KW - time series
UR - http://www.scopus.com/inward/record.url?scp=85135428385&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/gps.5787
DO - https://doi.org/10.1002/gps.5787
M3 - Article
C2 - 35929363
SN - 0885-6230
VL - 37
JO - International journal of geriatric psychiatry
JF - International journal of geriatric psychiatry
IS - 9
ER -