University of Groningen, University Medical Center Groningen, University Center Psychiatry (UCP) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands.
Department of Research and Education, Friesland Mental Health Care Services, Leeuwarden, The Netherlands.
BMC Med. 2020 Feb 18;18(1):36. doi: 10.1186/s12916-020-1500-9.
There is growing evidence that mental disorders behave like complex dynamic systems. Complex dynamic systems theory states that a slower recovery from small perturbations indicates a loss of resilience of a system. This study is the first to test whether the speed of recovery of affect states from small daily life perturbations predicts changes in psychopathological symptoms over 1 year in a group of adolescents at increased risk for mental disorders.
We used data from 157 adolescents from the TWINSSCAN study. Course of psychopathology was operationalized as the 1-year change in the Symptom Checklist-90 sum score. Two groups were defined: one with stable and one with increasing symptom levels. Time-series data on momentary daily affect and daily unpleasant events were collected 10 times a day for 6 days at baseline. We modeled the time-lagged effect of daily unpleasant events on negative and positive affect after each unpleasant event experienced, to examine at which time point the impact of the events is no longer detectable.
There was a significant difference between groups in the effect of unpleasant events on negative affect 90 min after the events were reported. Stratified by group, in the Increase group, the effect of unpleasant events on both negative (B = 0.05, p < 0.01) and positive affect (B = - 0. 08, p < 0.01) was still detectable 90 min after the events, whereas in the Stable group this was not the case.
Findings cautiously suggest that adolescents who develop more symptoms in the following year may display a slower affect recovery from daily perturbations at baseline. This supports the notion that mental health may behave according to the laws of a complex dynamic system. Future research needs to examine whether these dynamic indicators of system resilience may prove valuable for personalized risk assessment in this field.
越来越多的证据表明，精神障碍表现得像复杂的动态系统。复杂动态系统理论指出，一个系统从小的扰动中恢复得越慢，表明该系统的弹性就越低。本研究首次检验了在一组患有精神障碍风险增加的青少年中，从日常生活中小的扰动中恢复情绪状态的速度是否可以预测其在 1 年内的心理病理症状变化。
我们使用了来自 TWINSSCAN 研究的 157 名青少年的数据。精神病理学的发展过程表现为症状清单 90 项总分在 1 年内的变化。定义了两个组：一个是症状稳定组，另一个是症状增加组。在基线时，每天 10 次、连续 6 天收集关于瞬时日常情绪和每日不愉快事件的时间序列数据。我们对每次经历不愉快事件后，每日不愉快事件对负性和正性情绪的时滞效应进行建模，以检验在何时事件的影响不再可检测。
在报告不愉快事件后 90 分钟，两组之间不愉快事件对负性情绪的影响存在显著差异。按组分层，在增加组中，不愉快事件对负性（B=0.05，p<0.01）和正性情绪（B=-0.08，p<0.01）的影响在报告后 90 分钟仍可检测到，而在稳定组中则不然。
研究结果谨慎地表明，在接下来的一年中症状发展更多的青少年可能在基线时表现出从日常扰动中恢复情绪的速度较慢。这支持了心理健康可能遵循复杂动态系统规律的观点。未来的研究需要检验这些系统弹性的动态指标是否可以为该领域的个性化风险评估提供有价值的信息。
