Replication Data for: Look who is complaining: Psychological factors predicting subjective cognitive complaints in a large community sample of older adults

DOI

This dataset contains questionnaire data from 1219 adults from the general Dutch population aged 40 years or older. The data was collected online between October 2016 and March 2018. The goal was to examine the role of psychological factors in predicting subjective cognitive complaints in the domains of executive functioning, memory, and attention. For this purpose the following questionnaires were collected: Behavior Rating Inventory Executive Function - Adult version (BRIEF-A), Dutch version of the Memory Self-Efficacy Scale (MSEQ), Questionnaire for Experiences of Attention Deficits (German: Fragebogen Erlebter Defizite der Aufmerksamkeit [FEDA]), NEO-Five Factor Inventory (NEO-FFI), Depression Anxiety Stress Scale (DASS-21), and a demographic questionnaire. The demographic questionnaire contained questions about age, gender, education level, having a job, having a partner, having children, having pets, income, and body mass index. Additionally, questions about sleep, self-rated health, and quality of life were included.

Qualtrics, 2019

Identifier
DOI https://doi.org/10.34894/QNVTOA
Related Identifier https://doi.org/10.1080/23279095.2021.2007387
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/QNVTOA
Provenance
Creator Smit, Diede ORCID logo; Koerts, Janneke ORCID logo; Bangma, Dorien F. ORCID logo; Fuermaier, Anselm B.M. ORCID logo; Tucha, Lara I.; Tucha, Oliver M. ORCID logo
Publisher DataverseNL
Contributor Groningen Digital Competence Centre
Publication Year 2021
Funding Reference Internet fund and a Faculty grant (FG17.29) of the department of Psychology of the University of Groningen, the Netherlands
Rights CC0 Waiver; info:eu-repo/semantics/closedAccess; https://creativecommons.org/publicdomain/zero/1.0/
OpenAccess false
Contact Groningen Digital Competence Centre (University of Groningen)
Representation
Resource Type Survey data; Dataset
Format application/x-spss-sav; application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size 373534; 126482
Version 1.1
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences