Looking back and moving forward: dimensions of coping flexibility divergently predict long-term bereavement outcomes

Predicting levels of prolonged grief disorder symptoms during the COVID-19 pandemic: An integrated approach of classical data exploration, predictive machine learning, and explainable AI

BACKGROUND

Prior studies on Prolonged Grief Disorder (PGD) primarily employed classical approaches to link bereaved individuals' characteristics with PGD symptom levels. This study utilized machine learning to identify key factors influencing PGD symptoms during the COVID-19 pandemic.

METHODS

We analyzed data from 479 participants through an online survey, employing classical data exploration, predictive machine learning, and SHapley Additive exPlanations (SHAP) to determine key factors influencing PGD symptoms measured with the Traumatic Grief Inventory - Self Report (TGI-SR) from 19 variables, comparing five predictive models.

RESULTS

The classical approach identified eight variables associated with a possible PGD (TGI-SR score ≥ 59): unexpected causes of death, living alone, seeking professional support, taking anxiety and/or depression medications, using more grief services (telephone or online supports) and more confrontation-oriented coping strategies, and higher levels of depression and anxiety. Using machine learning techniques, the CatBoost algorithm provided the best predictive model of the TGI-SR score (r2 = 0.6479). The three variables influencing the most the level of PGD symptoms were anxiety, and levels of avoidance and confrontation coping strategies used.

CONCLUSIONS

This pioneering approach within the field of grief research enabled us to leverage the extensive dataset collected during the pandemic, facilitating a deeper comprehension of the predominant factors influencing the grieving process for individuals who experienced loss during this period.

LIMITATIONS

This study acknowledges self-selection bias, limited sample diversity, and suggests further research is needed to fully understand the predictors of PGD symptoms.

Experiences of Fathers in Norway Attending an Online Course on Therapeutic Writing After the Death of a Child

After the unexpected death of a child, bereaved parents require prompt access to helpful support systems. Online therapeutic writing courses can make such support accessible. Because few studies have included bereaved fathers as participants, we explored the experiences of fathers whose children died unexpectedly and who were part of an online course of therapeutic writing in Norway. We piloted two courses (group 1, six weeks, n = 9; group 2, 5 weeks, n = 5). We describe our methodological considerations for using poetic representations in qualitative health research and present four poetic representations based on fieldwork notes written by the principal investigator. Then, we triangulate and narratively analyze them together with two collective poems written by participants from each group; excerpts of the writings from two fathers, one per group; evaluation surveys (n = 4; n = 3); and, anonymous check-out journaling from the second group (n = 3). Resistance was a salient feature of our participants' grief, and writing enabled them to both be in contact with their emotional world and process difficult emotions as they looked for meaning despite the death of their children. Those who attended the most classes perceived the course as transformative, being part of an ongoing self-exploration, and a possibility to continue and strengthen the bond with their children. Our findings mirror the complexities of the grief experiences of fathers, giving account of their need to find a rhythm to dive into their emotional world, the importance of peer support, and the value of diversifying intervention techniques to meet individual needs and preferences.