TY - JOUR
T1 - Detecting Impending Symptom Transitions Using Early-Warning Signals in Individuals Receiving Treatment for Depression
AU - Helmich, Marieke A.
AU - Smit, Arnout C.
AU - Bringmann, Laura
AU - Schreuder, Marieke J.
AU - Oldehinkel, Albertine J.
AU - Wichers, Marieke
AU - Snippe, Evelien
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Drawing on dynamical systems theory, we investigated whether within-persons-detected early-warning signals in momentary affect preceded critical transitions toward lower levels of depressive symptoms during therapy. Participants were 41 depressed individuals who were starting psychological treatment. Positive and negative affect (high and low arousal) were measured 5 times a day using ecological momentary assessments over 4 months ( M = 522 observations per individual). Depressive symptoms were assessed weekly over 6 months. Within-persons rising autocorrelation was found for 89% of individuals with transitions in at least one variable (vs. 62.5% for individuals without transitions) and in a consistently higher proportion of the separate variables (~44% across affect measures) than for individuals without transitions (~27%). Rising variance was found for few individuals, both preceding transitions (~11%) and for individuals without transitions (~12%). Part of our sample showed critical slowing down, but early-warning signals may have limited value as a personalized prediction method.
AB - Drawing on dynamical systems theory, we investigated whether within-persons-detected early-warning signals in momentary affect preceded critical transitions toward lower levels of depressive symptoms during therapy. Participants were 41 depressed individuals who were starting psychological treatment. Positive and negative affect (high and low arousal) were measured 5 times a day using ecological momentary assessments over 4 months ( M = 522 observations per individual). Depressive symptoms were assessed weekly over 6 months. Within-persons rising autocorrelation was found for 89% of individuals with transitions in at least one variable (vs. 62.5% for individuals without transitions) and in a consistently higher proportion of the separate variables (~44% across affect measures) than for individuals without transitions (~27%). Rising variance was found for few individuals, both preceding transitions (~11%) and for individuals without transitions (~12%). Part of our sample showed critical slowing down, but early-warning signals may have limited value as a personalized prediction method.
UR - http://dx.doi.org/10.1177/21677026221137006
U2 - 10.1177/21677026221137006
DO - 10.1177/21677026221137006
M3 - Article
SN - 2167-7026
JO - Clinical Psychological Science
JF - Clinical Psychological Science
ER -