Trajectories of Insomnia Following Bereavement

DOI

This data package contains: Document describing data cleaning (in Dutch), Anonymized data for SPSS. Syntaxes and outputs belonging to the published article. Abstract from the paper: Insomnia symptoms are common following bereavement and may exacerbate severe and protracted grief reactions, such as prolonged grief disorder (PGD). However, typical trajectories of insomnia symptoms and risk factors for having a more chronic insomnia trajectory following bereavement are yet unknown. Method: In the current investigation, 220 recently bereaved (≤6 months post-loss) participants, completed questionnaires assessing sociodemographic and loss-related characteristics, rumination, experiential avoidance and symptoms of (prolonged) grief and depression, on three time-points (6 months apart). We applied growth mixture models to investigate the typical trajectories of insomnia symptoms following bereavement. Results: Three insomnia trajectory classes emerged, characterized by a resilient (47 %), recovering (43 %), and a chronic trajectory (10 %). Baseline depression symptoms best predicted the type of insomnia trajectory. At one-year follow-up, 9 %, 27 %, and 60 % of participants met the criteria for probable PGD within the resilient, recovering and chronic trajectory, respectively. A parallel process model showed that temporal changes in insomnia symptoms were strongly related to changes in prolonged grief symptoms. Conclusion: The results suggest, that targeting insomnia symptoms in the treatment of PGD, particularly with comorbid depression, may be a viable option.

Identifier
DOI https://doi.org/10.34894/HD0HAD
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/HD0HAD
Provenance
Creator de Lang, Thomas A. ORCID logo; Buyukcan-Tetik, Asuman (ORCID: 0000-0002-0541-702X); de Jong, Peter J. ORCID logo; Lancel, Marike; Eisma, M.C. ORCID logo
Publisher DataverseNL
Contributor Groningen Digital Compentence Centre
Publication Year 2024
Funding Reference NWO 016.veni195.113 ; VCVGZ 291
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Groningen Digital Compentence Centre (University of Groningen)
Representation
Resource Type Dataset
Format application/x-7z-compressed; application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size 99981; 1244808; 26420; 507546; 15441
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences