Delhom Iraida, Cholbi Aruca Calderón, Trejo Laura Lacomba
Teaching and Research Staff. Faculty of Health Sciences.Valencian International University. Pintor Sorolla Street, 21, 46002, Valencia, Spain.
Training and labor insertion technician in a Valencian Association of people with Intellectual Disabilities. Captains Galan and Garcia Hernández Square, 10, 46020, Valencia, Spain.
Eur Rev Appl Psychol. 2023 Jun 16:100912. doi: 10.1016/j.erap.2023.100912.
The presence of a mental or physical illness prior to the pandemic, the perceived threat from COVID-19, resilience or emotional intelligence may influence the onset or increase of psychopathology during the COVID-19 lockdown. The aim was to assess predictors of psychopathology by comparing two statistical methodologies (one linear and one non-linear).
A total of 802 Spanish participants (65.50% female) completed the questionnaires independently after signing informed consent. Psychopathology, perceived threat, resilience and emotional intelligence were assessed. Descriptive statistics, hierarchical regression models (HRM) and fuzzy set qualitative comparative analysis (fsQCA) were conducted.
The data obtained through the HRM showed that the presence of a previous mental illness, low resilience and emotional clarity, high emotional attention and repair, and COVID-19 threat perception predicted 51% of the variance in psychopathology. Results obtained from QCA showed that different combinations of these variables explained 37% of high levels of psychopathology and 86% of low levels of psychopathology, highlighting how the presence of prior mental illness, high emotional clarity, high resilience, low emotional attention and low perceived COVID-19 threat play a key role in explaining psychopathology.
These aspects will help promote personal resources to buffer psychopathology in lockdown situations.
在大流行之前存在精神或身体疾病、对新冠病毒的感知威胁、心理韧性或情商可能会影响新冠疫情封锁期间精神病理学的发作或增加。目的是通过比较两种统计方法(一种线性方法和一种非线性方法)来评估精神病理学的预测因素。
共有802名西班牙参与者(65.50%为女性)在签署知情同意书后独立完成问卷。对精神病理学、感知威胁、心理韧性和情商进行评估。进行了描述性统计、层次回归模型(HRM)和模糊集定性比较分析(fsQCA)。
通过HRM获得的数据表明,先前存在精神疾病、心理韧性低和情绪清晰度低、情绪关注度和修复度高以及对新冠病毒的威胁感知预测了精神病理学变异的51%。从QCA获得的结果表明,这些变量的不同组合解释了37%的高水平精神病理学和86%的低水平精神病理学,突出了先前存在精神疾病、高情绪清晰度、高心理韧性、低情绪关注度和低感知新冠病毒威胁在解释精神病理学方面如何发挥关键作用。
这些方面将有助于在封锁情况下促进个人资源以缓冲精神病理学。