Prognostic effects of selection, optimization and compensation strategies on work ability: results from the representative lidA cohort study on work, age, and health in Germany

  • Jeannette WeberEmail author
  • Andreas Müller
  • Michael Stiller
  • Daniela Borchart
Original Article



Regarding the increased need for the retention of older employees in the workforce, this study investigates whether there are main and interactive longitudinal effects of selection, optimization, compensation and working conditions according to the job demand–control model on work ability in older employees.


Longitudinal data of computer-assisted personal interviews with one follow-up after 3 years of 3961 participants (born in 1959 and 1965) of the representative German lidA cohort study was used. Multiple linear regressions were performed, analyzing prospective main and interactive effects of selection, optimization, compensation and working conditions during baseline on perceived work ability at follow-up.


Regarding selection, optimization and compensation, only compensation had a positive, but weak effect on work ability. Working conditions were more strongly related to work ability: decision authority and skill discretion had independent positive and job demands had independent negative effects on work ability. One interaction effect was observed between loss-based selection and decision authority, such that they mutually enhanced their positive effects on work ability. Only few and weak interactions among the sub-strategies, selection, optimization and compensation, were observed.


Results indicate that especially favorable working conditions in terms of high job control and low job demands, but also compensation might help older employees to maintain work ability.


Work ability Selection, optimization, compensation Working conditions Older workers Cohort study 



The research was financed in the frame of the lidA study by the German Federal Ministry of Education and Research (BMBF) under the Project Numbers 01 ER 0806, 01 ER 0825, 01 ER 0826, 01 ER 0827.

Compliance with ethical standards

Research involving human participants and/or animals

The research project was approved by the ethics committee of the University of Wuppertal (December 5th, 2008).

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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  1. Aguinis H (1995) Statistical power with moderated multiple regression in management research. J Manag 21:1141–1158. CrossRefGoogle Scholar
  2. Alcântara MA, Sampaio RF, Assunção A, Silva FCM (2014) Work Ability: using structural equation modeling to assess the effects of aging, health and work on the population of Brazilian municipal employees. Work (Reading Mass) 49:465–472Google Scholar
  3. Baltes PB, Baltes MM (1990) Psychological perspectives on successful aging: the model of selective optimization with compensation. In: Baltes PB, Baltes MM (eds) Successful aging: perspectives from the behavioral sciences. Cambridge University Press, New York, pp 1–34CrossRefGoogle Scholar
  4. Baltes PB, Baltes MM, Freund AM, Lang F (1999) The measurement of selection, optimization, and compensation (SOC) by self report: technical report 1999. Max-Planck-Institut für Bildungsforschung, Berlin, GermanyGoogle Scholar
  5. Baltes BB, Wynne K, Sirabian M, Krenn D, De Lange A (2014) Future time perspective, regulatory focus, and selection, optimization, and compensation: testing a longitudinal model. J Org Behav 35:1120–1133. CrossRefGoogle Scholar
  6. Becker A, Angerer P, Muller A (2017) The prevention of musculoskeletal complaints: a randomized controlled trial on additional effects of a work-related psychosocial coaching intervention compared to physiotherapy alone. Int Arch Occup Environ Health 90:357–371. CrossRefGoogle Scholar
  7. Bernburg M, Vitzthum K, Groneberg DA, Mache S (2016) Physicians’ occupational stress, depressive symptoms and work ability in relation to their working environment: a cross-sectional study of differences among medical residents with various specialties working in German hospitals. BMJ Open 6:e011369. CrossRefGoogle Scholar
  8. Bethge M, Radoschewski FM, Muller-Fahrnow W (2009) Work stress and work ability: cross-sectional findings from the German sociomedical panel of employees. Disabil Rehabil 31:1692–1699. CrossRefGoogle Scholar
  9. Bond FW, Bunce D (2001) Job control mediates change in a work reorganization intervention for stress reduction. J Occup Health Psychol 6:290–302CrossRefGoogle Scholar
  10. Bourbonnais R, Brisson C, Vezina M (2011) Long-term effects of an intervention on psychosocial work factors among healthcare professionals in a hospital setting. Occup Environ Med 68:479–486. CrossRefGoogle Scholar
  11. Cortina JM (1993) What is coefficient alpha? An examination of theory and applications. J Appl Psychol 78:98CrossRefGoogle Scholar
  12. Faulkner JA, Larkin LM, Claflin DR, Brooks SV (2007) Age-related changes in the structure and function of skeletal muscles. Clin Exp Pharmacol Physiol 34:1091–1096. CrossRefGoogle Scholar
  13. Fewtrell MS et al (2008) How much loss to follow-up is acceptable in long-term randomised trials and prospective studies? Arch Dis Child 93:458–461. CrossRefGoogle Scholar
  14. Freund AM, Baltes PB (1998) Selection, optimization, and compensation as strategies of life management: correlations with subjective indicators of successful aging. Psychol Aging 13:531–543CrossRefGoogle Scholar
  15. Freund AM, Baltes PB (2000) The orchestration of selection, optimization, and compensation: an action-theoretical conceptualization of a theory of developmental regulation. In: Perrig WJ, Grob A (eds) Control of human behaviour, mental processes and consciousness. Erlbaum, Mahwah, pp 35–58Google Scholar
  16. Freund AM, Baltes PB (2002) Life-management strategies of selection, optimization and compensation: measurement by self-report and construct validity. J Pers Soc Psychol 82:642–662CrossRefGoogle Scholar
  17. Hasselhorn H-M, Freude G (2007) Der Work-ability-Index: Ein Leitfaden. Wirtschaftsverl. NW, Verlag für Neue Wiss, BremerhavenGoogle Scholar
  18. Hasselhorn HM et al (2014) Cohort profile: the lidA Cohort Study—a German Cohort Study on work, age, health and work participation. Int J Epidemiol 43:1736–1749CrossRefGoogle Scholar
  19. Ihle A et al (2015) The role of cognitive resources for subjective work ability and health in nursing European. J Ageing 12:131–140. CrossRefGoogle Scholar
  20. Ilmarinen JE (2001) Aging workers. Occup Environ Med 58:546. CrossRefGoogle Scholar
  21. Ilmarinen J (2009) Work ability-a comprehensive concept for occupational health research and prevention. Scand J Work Environ Health 35:1–5CrossRefGoogle Scholar
  22. Ilmarinen J, Tuomi K (1992) Work ability of aging workers. Scand JWork Environ Health 18(Suppl 2):8–10Google Scholar
  23. Ilmarinen J, Tuomi K, Klockars M (1997) Changes in the work ability of active employees over an 11-year period. Scand J Work Environ Health 23(Suppl 1):49–57Google Scholar
  24. Karasek RA (1979) Job demands, job decision latitude, and mental strain: Implications for job redesign. Adm Sci Q, pp 285–308CrossRefGoogle Scholar
  25. Khan SS, Singer BD, Vaughan DE (2017) Molecular and physiological manifestations and measurement of aging in humans. Aging cell 16:624–633. CrossRefGoogle Scholar
  26. Koolhaas W, van der Klink JJ, de Boer MR, Groothoff JW, Brouwer S (2014) Chronic health conditions and work ability in the ageing workforce: the impact of work conditions, psychosocial factors and perceived health. Int Arch Occup Environ Health 87:433–443. CrossRefGoogle Scholar
  27. Leijon O, Balliu N, Lundin A, Vaez M, Kjellberg K, Hemmingsson T (2017) Effects of psychosocial work factors and psychological distress on self-assessed work ability: a 7-year follow-up in a general working population. Am J Ind Med 60:121–130. CrossRefGoogle Scholar
  28. Maatouk I et al (2018) Healthy ageing at work—efficacy of group interventions on the mental health of nurses aged 45 and older: results of a randomised, controlled trial. PLoS One 13:e0191000. CrossRefGoogle Scholar
  29. Mattila P, Elo A, Kuosma E, Kylä-Setälä E (2006) Effect of a participative work conference on psychosocial work environment and well-being. Eur J Work Organ Psychol 15:159–476. CrossRefGoogle Scholar
  30. Moghimi D, Zacher H, Scheibe S, Van Yperen NW (2017) The selection, optimization, and compensation model in the work context: a systematic review and meta-analysis of two decades of research. J Org Behav 38:247–275. CrossRefGoogle Scholar
  31. Montano D, Hoven H, Siegrist J (2014) Effects of organisational-level interventions at work on employees’ health: a systematic review. BMC Public Health 14:135. CrossRefGoogle Scholar
  32. Müller A (2016) Die Förderung der psychischen Gesundheit von Beschäftigten - Ein Überblick über die Wirksamkeit und Erfolgsfaktoren partizipativer verhältnisbezogener Interventionen. im Betrieb Wirtschaftspsychologie 18:40–47Google Scholar
  33. Müller A, Weigl M (2015) Selection, optimization, and compensation at work in relation to age. Encycl Geropsychol. CrossRefGoogle Scholar
  34. Müller A, Weigl M, Heiden B, Glaser J, Angerer P (2012) Promoting work ability and well-being in hospital nursing: the interplay of age, job control, and successful ageing strategies. Work (Reading Mass) 41(Suppl 1):5137–5144. CrossRefGoogle Scholar
  35. Müller A, Weigl M, Heiden B, Herbig B, Glaser J, Angerer P (2013) Selection, optimization, and compensation in nursing: exploration of job-specific strategies, scale development, and age-specific associations to work ability. J Adv Nurs 69:1630–1642. CrossRefGoogle Scholar
  36. Müller A, Heiden B, Herbig B, Poppe F, Angerer P (2016) Improving well-being at work: a randomized controlled intervention based on selection, optimization, and compensation. J Occup Health Psychol 21:169–181. CrossRefGoogle Scholar
  37. Müller A et al (2018) Bringing successful aging theories to occupational practice: is selective optimization with compensation trainable? Work Aging Retire 4:161–174. CrossRefGoogle Scholar
  38. Nübling M, Vomstein M, Nübling T, Stößel U, Hasselhorn H-M, Hofmann F (2011) Erfassung psychischer Belastungen anhand eines erprobten Fragebogens–Aufbau der COPSOQ-Datenbank. Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, Dortmund (Projektnummer F2031)Google Scholar
  39. Pohjonen T (2001) Perceived work ability of home care workers in relation to individual and work-related factors in different age groups. Occup Med (Oxford England) 51:209–217CrossRefGoogle Scholar
  40. Potočnik K (2017) Healthy ageing and well-being at work. In: Parry E, McCarthy J (eds) The palgrave handbook of age diversity and work. Palgrave Macmillan UK, London, pp 171–193. CrossRefGoogle Scholar
  41. Reynolds S (1997) Psychological well-being at work: Is prevention better than cure? J Psychosom Res 43:93–102. CrossRefGoogle Scholar
  42. Riedel N, Müller A, Ebener M (2015) Applying strategies of selection, optimization, and compensation to maintain work ability—a psychosocial resource complementing the job demand-control model? Results from the representative lida cohort study on work, age, and health in Germany. J Occup Environ Med 57:552–561. CrossRefGoogle Scholar
  43. Salonen P, Arola H, Nygard CH, Huhtala H, Koivisto AM (2003) Factors associated with premature departure from working life among ageing food industry employees. Occup Med (Oxford England) 53:65–68. CrossRefGoogle Scholar
  44. Salthouse TA (2013) Within-cohort age-related differences in cognitive functioning. Psychol Sci 24:123–130. CrossRefGoogle Scholar
  45. Sell L, Bultmann U, Rugulies R, Villadsen E, Faber A, Sogaard K (2009) Predicting long-term sickness absence and early retirement pension from self-reported work ability. Int Arch Occup Environ Health 82:1133–1138. CrossRefGoogle Scholar
  46. Siemsen E, Roth A, Oliveira P (2010) Common Method Bias in Regression Models With Linear, Quadratic, and Interaction Effects. Organ Res Methods 13:456–476. CrossRefGoogle Scholar
  47. Solem PE (2008) Age changes in subjective work ability. Int J Ageing Later Life 3:43–70CrossRefGoogle Scholar
  48. Spector PE, Brannick MT (2009) Common method variance or measurement bias? The problem and possible solutions. In: Buchanan D, Bryman A (eds) Handbook of organizational research methods, vol 10. Sage, London, pp 346–362Google Scholar
  49. Steinwede J, Kleugden M, Häring A, Schröder H (2015) Methodenbericht zur Haupterhebung lidA - leben in der Arbeit, 2. Welle. Forschungsdatenzentrum (FDZ) der Bundesagentur. für Arbeit im Institut für Arbeitsmarkt- und Berufsforschung, NürnbergGoogle Scholar
  50. Tuomi K, Ilmarinen J, Eskelinen L, Jarvinen E, Toikkanen J, Klockars M (1991) Prevalence and incidence rates of diseases and work ability in different work categories of municipal occupations Scand. J Work Environ Health 17(Suppl 1):67–74Google Scholar
  51. Tuomi K, Ilmarinen J, Jahkola A, Katajarinne L, Tulkki A (1999) Work ability index, 2nd edn. Finnish Institute of Occupational Health, HelsinkiGoogle Scholar
  52. van de Vijfeijke H et al (2013) Differential effects of mental and physical health and coping style on work ability: a 1-year follow-up study among aging workers. J Occup Environ Med Am Coll Occup Environ Med 55:1238–1243. CrossRefGoogle Scholar
  53. van den Berg TI, Elders LA, de Zwart BC, Burdorf A (2009) The effects of work-related and individual factors on the Work Ability Index: a systematic review. Occup Environ Med 66:211–220. CrossRefGoogle Scholar
  54. von Bonsdorff ME, von Bonsdorff MB, Zhou ZE, Kauppinen M, Miettinen M, Rantanen T, Vanhala S (2014) Organizational justice, selection, optimization with compensation, and nurses’ work ability. J Occup Environ Med Am Coll Occup Environ Med 56:326–330. CrossRefGoogle Scholar
  55. Weigl M, Müller A, Hornung S, Zacher H, Angerer P (2013) The moderating effects of job control and selection, optimization, and compensation strategies on the age-work ability relationship. Jo Org Behav 34:607–628CrossRefGoogle Scholar
  56. Wiese BS, Freund AM, Baltes PB (2000) Selection, optimization, and compensation: an action-related approach to work and partnership. J Vocat Behav 57:273–300CrossRefGoogle Scholar
  57. Wiese BS, Freund AM, Baltes PB (2002) Subjective career success and emotional well-being: longitudinal predictive power of selection, optimization and compensation. J Vocat Behav 60:321–335CrossRefGoogle Scholar
  58. Wirth H, Gresch C, Müller W, Pollak R, Weiss F (2009) Validating the ESeC-scheme as operationalization of social class: The case of Germany vol Arbeitspapiere - Mannheimer Zentrum für Europäische Sozialforschung: 119. MannheimGoogle Scholar
  59. Yeung DY, Fung HH (2009) Aging and work: How do SOC strategies contribute to job performance across adulthood? Psychol Aging 24:927–940CrossRefGoogle Scholar
  60. Zacher H, Chan F, Bakker AB, Demerouti E (2015) Selection, optimization, and compensation strategies: Interactive effects on daily work engagement. J Vocat Behav 87:101–107. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Occupational, Social and Environmental Medicine, Centre for Health and SocietyHeinrich-Heine-University of DüsseldorfDüsseldorfGermany
  2. 2.Institute of Psychology, Work- and Organizational PsychologyUniversity Duisburg-EssenEssenGermany
  3. 3.Department of Occupational Health Science, School of Mechanical Engineering and Safety EngineeringUniversity of WuppertalWuppertalGermany

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