Work-related stress assessed by a text message single-item stress question
Open accessAbstract
BACKGROUND: Given the prevalence of work stress-related ill-health in the Western world, it is important to find cost-effective, easy-to-use and valid measures which can be used both in research and in practice. AIMS: To examine the validity and reliability of the single-item stress question (SISQ), distributed weekly by short message service (SMS) and used for measurement of work-related stress. METHODS: The convergent validity was assessed through associations between the SISQ and subscales of the Job Demand-Control-Support model, the Effort-Reward Imbalance model and scales measuring depression, exhaustion and sleep. The predictive validity was assessed using SISQ data collected through SMS. The reliability was analysed by the test-retest procedure. RESULTS: Correlations between the SISQ and all the subscales except for job strain and esteem reward were significant, ranging from -0.186 to 0.627. The SISQ could also predict sick leave, depression and exhaustion at 12-month follow-up. The analysis on reliability revealed a satisfactory stability with a weighted kappa between 0.804 and 0.868. CONCLUSIONS: The SISQ, administered through SMS, can be used for the screening of stress levels in a working population.
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The SISQ is a validated single-item measure for screening stress levels in a working population.
“The SISQ is a single-item measure of current stress on a 5-point Likert scale from 1 (“Not at all”) to 5 (“Very much”) and has been validated for the screening of stress levels in a working population [25].”
From A pilot evaluation of a smartphone application for workplace depression (2020) · cites this paper as [25]
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- Authors
- Arapovic-Johansson, B., Wåhlin, C., Kwak, L., Björklund, C., & Jensen, I.
- Affiliations
- Karolinska Institutet (SE)
- Linköping University (SE)
- Corresponding author
- Arapovic-Johansson, B
- Venue
- Occupational Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-08-18
- Volume
- 67
- Issue
- 8
- Pages
- 601-608
- ISSN
- 0962-7480 (ISSN-L)
- 1471-8405
- PMC
- PMC5927000
- OpenAlex
- W2747728381
- Cited by
- 68
- References
- 22
- Citations by year
- 2026: 11 · 2025: 9 · 2024: 10 · 2023: 6 · 2022: 12 · 2021: 6 · 2020: 6 · 2019: 3 · 2018: 1 · 2017: 2 · 2016: 1
- FWCI
- 5.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Occupational Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DiVA (Linkoping University) (submittedVersion, other-oa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Workplace Health and Well-being
- Social Sciences › Psychology › Social Psychology › Stress and Burnout Research
- Social Sciences › Psychology › Social Psychology › Technostress in Professional Settings
- Keywords
- occupational stress, short message service, text messaging, stress screening, demand-control-support model, effort-reward imbalance model, convergent validity, predictive validity, test-retest reliability, sick leave, depression, exhaustion, sleep, occupational health surveillance
- MeSH terms
- Adult, Female, Humans, Male, Middle Aged, Surveys and Questionnaires, Stress, Psychological, Reproducibility of Results, Workplace, Sick Leave, Diagnostic Techniques and Procedures, Text Messaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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