Primary data from the German Job Search Panel
Work, Organizational and Business PsychologyAuthors(s) / Creator(s)
Hetschko, ClemensEid, Michael
Lawes, Mario
Schmidtke, Julia
Stephan, Gesine
Schöb, Ronnie
Abstract
The aim of this research project was to gain a detailed understanding of the effects of unemployment on well-being and health. To this end, two cohorts of jobseekers - one before and one during the COVID-19 pandemic - were invited to take part in a monthly smartphone-based survey between 2017 and 2021. In a subsample, cortisol in the hair was also determined as a biomarker for chronic stress. Participants were surveyed monthly for up to two years using a smartphone app about their well-being, health and job status, among other things. If the respondents agreed to this, a link to the process data of the Federal Employment Agency is possible. Two methodological reports by Hetschko et al. (2022) and Schmidtke et al. (2023) describe the survey process and selection into the survey in detail. In total, almost 1,900 people initially took part in a first cohort and almost 1,000 people in a second cohort of the ‘German Job Search Panel’ (GJSP).
Persistent Identifier
https://doi.org/10.5160/psychdata.lsmo21ge02Year of Publication
2024Funding
German Research Foundation (reference numbers: EI 379/11-1, EI 379/11-2, SCHO 1270/5-1, SCHO 1270/5-2, STE 1424/4-1 und STE 1424/4-2)Citation
Hetschko, C., Eid, M., Lawes, M., Schmidtke, J., Stephan, G. . & Schöb, R. (2024). Primary data from the German Job Search Panel (Version 1.0.0) [Data and Documentation]. Trier: Research Data Center at ZPID. https://doi.org/10.5160/psychdata.lsmo21ge02Study Description
Research Questions/Hypotheses:
This is a large interdisciplinary project in which no specific hypotheses have been formulated.
Research Design:
Mixed standardized survey instrument (combination of differently standardized parts); repeated measurements
Measurement Instruments/Apparatus:
The following measurement instruments were used: Monthly smartphone-based surveys; details on the frequency of the various questionnaires can be found in the methodological report (Hetschko et al., 2022) and in the codebook on the OSF website (https://osf.io/h4f25/).
Data Collection Method:
Survey in the absence of an investigator
- Other method, namely: Smartphone-based survey
Population:
Survey Time Period:
2017-11 - 2019-05 (cohort 1); 2020-07 - 2021-02 (cohort 2)
Sample:
All persons who were likely to have registered as jobseekers due to a mass layoff or plant closure were contacted. In addition, for the first cohort, a random sample of people were contacted who came from companies that had probably not carried out mass layoffs or plant closures (random sample). Details are described in Hetschko et al. (2022).
Gender Distribution:
female participants (cohort 1: N = 793; cohort 2: N = 423)
male participants (cohort 1: N = 743; cohort 2: N = 483)
other (cohort 1: N = 4; cohort 2: N = 2)
not specified (cohort 1: N = 0; cohort 2: N = 1)
Age Distribution:
Cohort 1: 19 - 60 (at the beginning of the survey); Cohort 2: 20 - 60 (at the beginning of the survey)
Spatial Coverage (Country/Region/City): Germany/-/-
Subject Recruitment:
To recruit participants, between November 2017 and May 2019 (first cohort; before the COVID-19 pandemic) and July 2020 and February 2021 (second cohort; during the COVID-19 pandemic), people who had registered as jobseekers with the Federal Employment Agency in the preceding weeks were invited by letter or email each month. The project took advantage of the fact that people who want to apply for unemployment benefits in Germany must register as jobseekers three months before the end of their employment relationship. If they learn of the end of their employment later, they must register within three days. The study only included people who were no longer in their probationary period at the time of registering as jobseekers, were of German nationality and aged between 18 and 60. Details on recruitment can be found in Hetschko et al. (2022).
Sample Size:
N = 1540 (cohort 1), N = 909 (cohort 2)
Return/Drop Out:
MD5: 597aa86386849ddc78f145314fe0614c
MD5: 4cdd737f84d550fd6bfdcc01a9532f62
MD5: 1969a6d76c476c93479ab6c70d5587b2
MD5: ee2f9984b55dc8e696638f505f285b94
MD5: f14666fb731520134112592d9c478dd0
MD5: 8883320dbdeda5e0a8029cc23a994870
MD5: f9d948fb30bd4d05fb3de0688a34b4ec
MD5: 222bf6062bb728e319753514495f10b7
MD5: 723cd14ac708cdb0f9a6db0011f34019
MD5: 26816890187b2460199961bd78eb0625
MD5: 8c7dd9a56be890db47d2aaa8417ad75b
MD5: f8fe3c0bcd01b08fc143a61a9c3eac03
MD5: cd5c91dfbe16e5db8e82a44c46690e69
MD5: ce089339c431d9004ad7e3299c40d1eb
MD5: 0fa11403e671cbfec58746b7f41353d6
MD5: 7156df48fcd5b273255541d2f0edf5cb
MD5: 7d19eb5ae9c0df28e5ea4764fa49e58a
MD5: 96cad72e5801ecc4caca9f8e9f9d9fcd
MD5: c3908e1f079d006975019967e1559a43
MD5: a285766c1736b230ba39f78c883093f7
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