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Monitoring emotional intensity and variability to forecast depression recurrence in real time in remitted adults.
Journal of Consulting and Clinical Psychology ( IF 4.5 ) Pub Date : 2024-03-21 , DOI: 10.1037/ccp0000871
Marieke J Schreuder 1 , Evelien Schat 1 , Arnout C Smit 2 , Evelien Snippe 3 , Eva Ceulemans 1
Affiliation  

OBJECTIVE Recurrent depressive episodes are preceded by changing mean levels of repeatedly assessed emotions (e.g., feeling restless), which can be detected in real time using statistical process control (SPC). This study investigated whether monitoring changes in the standard deviation (SD) of emotions and negative thinking improves the early detection of recurrent depression. METHOD Formerly depressed adults (N = 41) monitored their emotions five times a day for 4 consecutive months. During the study, 22 individuals experienced recurrent depression. We used SPC to detect warning signs (i.e., changing means and SDs) of four emotions (positive and negative affect with high or low arousal) and negative thinking. RESULTS SD-based warning signs only preceded 23%-36% of recurrences, but almost never reflected a false alarm (0%-16%). Correspondingly, SD-based warnings had a high specificity (at the cost of sensitivity), while mean-based warnings had a higher sensitivity (but lower specificity). There was little overlap in mean- and SD-based warning signs. For the majority of emotions, monitoring for high SDs alongside monitoring changes in mean levels improved the detection of depression (p < .015) compared to when only monitoring for changing mean levels. CONCLUSIONS Warning signs for depression manifest not only in changing mean levels of emotions and cognitions but also in increasing SDs. These warnings could eventually be used to detect not just who is at increased risk for depression but also when risk is rising. Further research is needed to evaluate the clinical utility of depression SPC. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译:


监测情绪强度和变异性,以实时预测缓解后的成年人抑郁症的复发。



目的 复发性抑郁发作之前,反复评估的情绪(例如,感到不安)的平均水平会发生变化,这可以使用统计过程控制(SPC)实时检测到。本研究调查了监测情绪和消极思维标准差(SD)的变化是否可以改善复发性抑郁症的早期发现。方法 曾经患有抑郁症的成年人 (N = 41) 每天监测自己的情绪五次,连续 4 个月。在研究期间,22 个人经历了复发性抑郁症。我们使用 SPC 来检测四种情绪(具有高或低唤醒度的积极和消极影响)和消极思维的警告信号(即改变均值和 SD)。结果 基于 SD 的警告信号仅出现在 23%-36% 的复发之前,但几乎从未反映出误报 (0%-16%)。相应地,基于 SD 的警告具有较高的特异性(以敏感性为代价),而基于平均值的警告具有较高的敏感性(但特异性较低)。基于平均值和标准差的警告信号几乎没有重叠。对于大多数情绪,与仅监测平均水平变化相比,监测高 SD 并监测平均水平变化可以改善抑郁症的检测 (p < .015)。结论 抑郁症的警告信号不仅体现在情绪和认知平均水平的变化上,而且还体现在标准差的增加上。这些警告最终不仅可以用于检测哪些人患抑郁症的风险增加,还可以用于检测风险何时上升。需要进一步的研究来评估抑郁症 SPC 的临床效用。 (PsycInfo 数据库记录 (c) 2024 APA,保留所有权利)。
更新日期:2024-03-21
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