Simoes Jorge, Bulla Jan, Neff Patrick, Pryss Rüdiger, Marcrum Steven C, Langguth Berthold, Schlee Winfried
Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany.
Department of Mathematics, University of Bergen, Bergen, Norway.
Front Neurosci. 2022 Jul 5;16:883665. doi: 10.3389/fnins.2022.883665. eCollection 2022.
Tinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a better understanding of tinnitus by capturing the fluctuations of tinnitus symptoms, such as distress and loudness, and psychological processes, such as emotional arousal, overall stress, mood, and concentration and how these variables interact over time. Whether any of those variables have an influence over the next day, that is, whether any of these variables are auto- or cross-correlated, is still unanswered.
Assess whether behavioral and symptom-related data from tinnitus users from the TrackYourTinnitus (TYT) mobile app have an impact on tinnitus loudness and distress on subsequent days.
Anonymized data was collected from 278 users of the iOS or Android TYT apps between 2014 and 2020. Tinnitus-related distress, tinnitus loudness, concentration level, mood, emotional arousal, and overall stress level were assessed using either a slider or the Wong-Baker Pain FACES scale a daily survey. Three modeling strategies were used to investigate whether tinnitus loudness and distress are affected by previous days symptoms or psychological processes: auto- and cross correlations, regressions with elastic net regularization, and subgrouping within group iterative multiple model estimation (S-GIMME).
No autocorrelation or cross-correlation was observed at the group level between the variables assessed. However, application of the regression models with elastic net regularization identified individualized predictors of tinnitus loudness and distress for most participants, with the models including contemporaneous and lagged information from the previous day. S-GIMME corroborated these findings by identifying individualized predictors of tinnitus loudness and distress from the previous day.
We showed that tinnitus loudness and tinnitus distress are affected by the contemporaneous and lagged dynamics of behavioral and emotional processes measured through EMA. These effects were seen at the group, and individual levels. The relevance EMA and the implications of the insights derived from it for tinnitus care are discussed, especially considering current trends toward the individualization of tinnitus care.
耳鸣是一种异质性疾病,可能与中度至重度残疾相关,但只有一部分人受该疾病困扰的原因尚不完全清楚。生态瞬时评估(EMA)通过捕捉耳鸣症状(如痛苦和响度)以及心理过程(如情绪唤醒、总体压力、情绪和注意力)的波动,以及这些变量如何随时间相互作用,从而有助于更好地理解耳鸣。这些变量是否会对第二天产生影响,即这些变量是否存在自相关或交叉相关,仍然没有答案。
评估来自“追踪你的耳鸣”(TYT)移动应用程序的耳鸣用户的行为和症状相关数据是否会对随后几天耳鸣的响度和痛苦程度产生影响。
在2014年至2020年期间,从278名iOS或安卓版TYT应用程序用户中收集了匿名数据。使用滑块或Wong-Baker面部表情疼痛量表通过每日调查评估与耳鸣相关的痛苦、耳鸣响度、注意力水平、情绪、情绪唤醒和总体压力水平。采用三种建模策略来研究耳鸣响度和痛苦是否受到前几天症状或心理过程的影响:自相关和交叉相关、弹性网正则化回归以及组内迭代多模型估计中的亚组分析(S-GIMME)。
在评估的变量之间,未在组水平上观察到自相关或交叉相关。然而,应用弹性网正则化回归模型为大多数参与者确定了耳鸣响度和痛苦的个体化预测因素,这些模型包括前一天的同期和滞后信息。S-GIMME通过确定前一天耳鸣响度和痛苦的个体化预测因素证实了这些发现。
我们表明,耳鸣响度和耳鸣痛苦受到通过EMA测量的行为和情绪过程的同期和滞后动态的影响。这些影响在组和个体水平上均可见。讨论了EMA的相关性及其对耳鸣护理的启示,特别是考虑到当前耳鸣护理个体化的趋势。