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The Standard Stress Scale (SSS): Measuring Stress in the Life Course

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Methodological Issues of Longitudinal Surveys

Abstract

This contribution presents the Standard Stress Scale (SSS), a new scale that has been specially developed to meet the requirements of multicohort panel studies— such as the National Educational Panel Study (NEPS)—that refer to the whole life course. Accordingly, the SSS is consistently applicable for different age groups from 14 years old onwards and is also suitable for a wide range of people, irrespective of their stage in life and employment situation. The items are applicable to (university) students; employed, unemployed, and self-employed people; housewives and -husbands; old-age pensioners; and so forth. To obtain the final 11-item Standard Stress Scale (SSS), 35 questions regarding stressful life situations, social stress, daily distress, anxiety about the future, and other stresses and strains were developed following the theoretical approach of the effort-reward imbalance model (ERI) and the demand-control model. These 35 items were pretested with different subsamples—such as students in different school types, university students, and adults—using self-administered questionnaires. The total sample of the pretest includes 372 respondents. All of the 35 original questions had a small item-nonresponse rate and a good variance among respondents. Using factor analyses, the questions with the highest factor loading in each of the dimensions were used to represent the final 11-item SSS. In some cases, when the questions with the highest loading did not perform well in the cognitive pretest, the item with the second-highest loading was chosen instead. Although the most distinct items were selected, the final 11 items of the SSS show good reliability values. The Cronbach’s Alpha values vary in a range in all subsamples from 0.58 for the unemployed to 0.66 for students. In addition, further analyses show a high correlation of the final SSS with self-rated health. The use of the SSS is free of charge but has to be cited using this publication.

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References

  • Backé, E.-M., Seidler, A., Latza, U., Rossnagel, K., & Schumann, B. (2012). The role of psychosocial tress at work for the development of cardiovascular diseases: A systematic review. International Archives of Occupational and Environmental Health, 85, 67–79. doi:10.1007/s00420-011-0643-6

    Google Scholar 

  • Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2003). Multivariate Analysemethoden. Eine anwendungsorientierte Einführung. Heidelberg: Springer.

    Google Scholar 

  • Chandola, T., Marmot, M., & J. Siegrist (2007). Failed reciprocity in close social relationships and health: Findings from the Whitehall II study. Journal of Psychosom Research, 63, 403 – 411. doi: 10.1016/j.jpsychores.2007.07.012

    Google Scholar 

  • Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 1 – 9.

    Google Scholar 

  • Gross, C., & Seebaß, K. (2012). Eine neue Skala zur Messung von Stress im Lebensverlauf. Qualitätsbericht zu Erhebungsdesign und Methodik für NEPS. Unpublished manuscript.

    Google Scholar 

  • Fliege, H., Rose, M., Arck, P., Levenstein, S., & Klapp, B. F. (2001). Validierung des “Perceived Stress Questionnaire” (PSQ) an einer deutschen Stichprobe. Diagnostica, 47, 142–152. doi:10.1026//0012-1924.47.3.142

    Google Scholar 

  • Fliege, H., Rose, M., Arck, P., Walter, O. B., Kocalevent, R. D., Weber, C., & Klapp, B. F. (2005). The Perceived Stress Questionnaire (PSQ) reconsidered: Validation and reference values from different clinical and healthy adult samples. Psychosomatic Medicine, 67, 78 – 88. doi:10.1097/01.psy.0000151491.80178.78

    Google Scholar 

  • Frese, M., & Zapf, D. (1987). Eine Skala zur Erfassung von sozialen Stressoren am Arbeitsplatz. Zeitschrift für Arbeitswissenschaften, 41(3), 134 – 141.

    Google Scholar 

  • Holmes, T. H., & Rahe, R. H. (1967). The social readjustment rating scale. Journal of Psychosomatic Research, 11, 213 – 218. doi:10.1016/0022-3999(67)90010-4

    Google Scholar 

  • Karasek, R., & Theorell, T. (1990). Healthy work, stress, productivity, and the reconstruction of working life. New York: Basic Books.

    Google Scholar 

  • Kocalevent, R.-D., Hinz, A., Brähler, E., & Klapp, B. F. (2011). Regionale und individuelle Faktoren von Stresserleben in Deutschland: Ergebnisse einer repräsentativen Befragung mit dem Perceived Stress Questionnaire (PSQ). Gesundheitswesen, 73, 829–834. doi:10.1055/s-0030-1268445

    Google Scholar 

  • Levenstein, S., Prantera C., Varvo V., Scribano, M. L., Berto, E., Luzi, C., & Andreoli, A. (1993). Development of the Perceived Stress Questionnaire: A new tool for psychosomatic research. Journal of Psychosomatic Research, 37, 19–32. doi:022-3999/93

    Google Scholar 

  • Li, J., Shang, L., Wang, T., & Siegrist, J. (2010). Measuring effort—reward imbalance in school settings: A novel approach and its association with self-rated health. Journal of Epidemiology, 20, 111 – 118. doi:10.2188/jea.JE20090057

    Google Scholar 

  • Niedhammer, I., Tek, M.-L., Starke, D., & Siegrist, S. (2004). Effort—reward imbalance model and self-reported health: Cross-sectional and prospective findings from the GAZEL cohort. Social Science & Medicine, 58, 1531–1541. doi:10.1016/S0277-9536(03)00346-0

    Google Scholar 

  • Schulz, J., Jansen, L. J., & Schlotz, W. (2005). Stressreaktivität: Theoretisches Konzept und Messung. Diagnostica, 51, 124–133. doi:10.1026/0012-1924.51.3.124

    Google Scholar 

  • Schulz, P., Schlotz, W., & Becker, P. (2004). TICS Trier Inventar zum chronischen Stress. Göttingen: Hogrefe.

    Google Scholar 

  • Siegrist, J. (1996). Soziale Krisen und Gesundheit. Eine Theorie der Gesundheitsförderung am Beispiel von Herz-Kreislauf-Risiken im Erwerbsleben. Göttingen: Hogrefe.

    Google Scholar 

  • Siegrist, J., Starke, D., Chandola, T., Godin, I., Marmot, M., Niedhammer, I., & Peter, R. (2004). The measurement of effort—reward imbalance at work: European comparisons. Social Science & Medicine, 58, 1483 – 1499. doi:10.1016/S0277-9536(03)00351-4

    Google Scholar 

  • Siegrist, J., Wege, N., Pühlhofer, F., & Wahrendorf, M. (2008). A short generic measure of work stress in the era of globalization: Effort—reward imbalance. International Archives of Occupational and Environmental Health, 82, 1005 – 1013. doi:10.1007/s00420-008-0384–3

    Google Scholar 

  • Sperlich S., Peter, R. & Geyer, S. (2012). Applying the effort-reward imbalance model to household and family work: A population-based study of German mothers. BMC Public Health, 12, 1 – 12. doi: 10.1186/1471-2458-12-12

    Google Scholar 

  • Sperlich, S., Arnhold-Kerri, S., Siegrist, J., & Geyer, S. (2013). The mismatch between high effort and low reward in household and family work predicts impaired health among mothers. European Journal of Public Health, 23, 893–898. doi: 10.1093/eurpub/cks134

    Google Scholar 

  • Steptoe, A. (1991). The links between stress and illness. Journal of Psychosomatic Research, 35, 633 – 644. doi:022-3999/91

    Google Scholar 

  • Wolff, H.-G., & Bacher, J. (2010). Hauptkomponentenanalyse und explorative Faktorenanalyse. In C. Wolf, & H. Best. (Eds.), Handbuch der sozialwissenschaftlichen Datenanalyse (S. 333–366). Wiesbaden: Springer.

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Correspondence to Christiane Gross or Katharina Seebaß .

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Gross, C., Seebaß, K. (2016). The Standard Stress Scale (SSS): Measuring Stress in the Life Course. In: Blossfeld, HP., von Maurice, J., Bayer, M., Skopek, J. (eds) Methodological Issues of Longitudinal Surveys. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-11994-2_14

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  • DOI: https://doi.org/10.1007/978-3-658-11994-2_14

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