Cross-Lagged Analyses of Prolonged Grief and Depression Symptoms with Insomnia Symptoms

DOI

This data package contains: Document describing data cleaning (in Dutch), Anonymized data for SPSS. Syntaxes and outputs belonging to the published article: 2 SPSS syntaxes. One for general analyses and one for creating Mplus data file. Mplus output files ((per analysis) output files contain the syntaxes).

Abstract from paper: Prolonged grief disorder, characterized by severe, persistent and disabling grief, has recently been added to the DSM-5-TR and ICD-11. Treatment for prolonged grief symptoms shows limited effectiveness. It has been suggested that prolonged grief symptoms exacerbate insomnia symptoms, whereas insomnia symptoms, in turn, may fuel prolonged grief symptoms. To help clarify if treating sleep disturbances may be a viable treatment option for prolonged grief disorder, we examined the proposed reciprocal relationship between symptoms of prolonged grief and insomnia. On three time points across six-month intervals, 343 bereaved adults (88% female) completed questionnaires to assess prolonged grief, depression, and insomnia symptoms. We applied random intercept cross-lagged panel models (RICLPMs) to assess reciprocal within-person effects between prolonged grief and insomnia symptoms and, as a secondary aim, between depression and insomnia symptoms. Changes in insomnia symptoms predicted changes in prolonged grief symptoms but not vice versa. Additionally, changes in depression and insomnia symptoms showed a reciprocal relationship. Our results suggest that targeting insomnia symptoms after bereavement is a viable option for improving current treatments for prolonged grief disorder.

Identifier
DOI https://doi.org/10.34894/K7IKFA
Related Identifier https://doi.org/10.1016/j.beth.2022.12.004
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/K7IKFA
Provenance
Creator de Lang, Thomas ORCID logo
Publisher DataverseNL
Contributor Digital Competence Centre
Publication Year 2023
Funding Reference NWO, 016 veni195 113; VCVGZ, 291
Rights info:eu-repo/semantics/restrictedAccess
OpenAccess false
Contact Digital Competence Centre (University of Groningen)
Representation
Resource Type Dataset
Format application/x-7z-compressed; application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size 98046; 1244809; 330187; 96054; 15751
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