| Popis: |
Variation exists in how people respond to the loss of a loved one. For most people, grief reactions will naturally decrease over time. Yet, approximately 10% of people bereaved by a natural cause (Lundorff et al., 2017) and 50% of the people bereaved by an unnatural cause (Djelantik et al., 2020) develops intense and disabling grief symptoms associated with significant distress interfering with daily functioning. These grief symptoms are referred to as prolonged grief disorder (PGD) in the DSM-5-TR (APA, 2022). PGD is characterized by persistent yearning/longing for the deceased, and preoccupation with thoughts or memories of the deceased for at least twelve months after the death of a loved one. Due to the potential traumatic characteristics of losses during the COVID-19 pandemic, it is expected that PGD prevalence will be high (Kokou-Kpolou et al., 2020). In line with this expectation, preliminary results demonstrated that (acute) PG is high in people bereaved during the COVID-19 pandemic (Breen et al., 2022), compared to people bereaved before the COVID-19 pandemic (Downar et al., 2022; Eisma & Tamminga, 2020). To date, most studies evaluating grief levels in people bereaved during the COVID-19 pandemic have focused on the presence or absence of psychopathology. However, mental health not only encompasses less psychopathology, but also increased well-being. The dual-continua model of mental health by Keyes (2005) holds that psychopathology and well-being are related, yet distinct dimensions. Accordingly, the absence of psychopathology does not imply the presence of well-being and vice versa. This is why focusing only on the presence or absence of psychopathology gives an overly one-sided picture of mental health. In addition, psychological disorders have often been studied dichotomously (i.e., absent or present) by reporting on prevalence rates or have been studied using symptom-level means. Consequently, individual differences in psychological responses are not taken into account, while research suggests that there are considerable differences in psychological responses between individuals (e.g., Boelen et al., 2019; Djelantik et al., 2018; Eisma et al., 2019; Nielsen et al., 2019). A statistical method that can be used to identify subgroups of people that vary in response patterns is latent class analysis (LCA). LCA classifies people into unobserved subgroups (i.e., latent classes) based on similar response patterns. So far, one prior LCA study identified latent classes of bereaved people based on both negative (i.e., PGD symptoms) and positive (i.e., post-traumatic growth (PTG)) psychological outcomes (Zhou et al., 2018). They found three latent classes: one class characterized by low/moderate PGD and low/moderate PTG, a second class characterized by low/moderate PGD and high PTG, and a third class characterized by moderate/high PGD and high PTG. To our understanding, no studies have yet been conducted examining classes of bereaved people in terms of indicators of PGD and well-being. However, it is likely that latent classes of bereaved people can be identified based on differences in their endorsement of different indicators of PGD and well-being. Accordingly, the first aim of our study is to examine if, among Dutch people who lost a loved one during the COVID-19 pandemic, heterogeneous latent classes can be identified that differ in terms of the endorsement of these indicators. The second aim of our study is to examine correlates (i.e., socio-demographic, pandemic-related, health-related, and trauma exposure characteristics) of class membership. |
