Quality of Life Research

, Volume 27, Issue 2, pp 423–436 | Cite as

Assessing reserve-building pursuits and person characteristics: psychometric validation of the Reserve-Building Measure

  • Carolyn E. SchwartzEmail author
  • Wesley Michael
  • Jie Zhang
  • Bruce D. Rapkin
  • Mirjam A. G. Sprangers



A growing body of research suggests that regularly engaging in stimulating activities across multiple domains—physical, cultural, intellectual, communal, and spiritual—builds resilience. This project investigated the psychometric characteristics of the DeltaQuest Reserve-Building Measure for use in prospective research.


The study included Rare Patient Voice panel participants. The web-based survey included the Reserve-Building Measure with one-week re-test, measures of quality of life (QOL) and well-being (PROMIS General Health; NeuroQOL Cognitive Function and Positive Affect & Well-Being short-forms; Ryff Environmental Mastery subscale); and the Big Five Inventory-10 personality measure. Classical test theory and item response theory (IRT) analyses investigated psychometric characteristics of the Reserve-Building Measure.


This North American sample (n = 592) included both patients and caregivers [mean age = 44, SD 19)]. Psychometric analyses revealed distinct subscales measuring current reserve-building activities (Active in the World, Games, Outdoors, Creative, Religious/Spiritual, Exercise, Inner Life, Shopping/Cooking, Passive Media Consumption,), past reserve-building activities (Childhood Activities, Achievement), and reserve-related person-factors (Perseverance, Current and Past Social Support, and Work Value). Test–retest stability (n = 101) was moderately high for 11 of 15 subscales (ICC range 0.78–0.99); four were below 0.59 indicating a need for further refinement. IRT analyses supported the item functioning of all subscales. Correlational analyses suggest the measure’s subscales tap distinct constructs (range r = 0.11–0.46) which are not redundant with QOL, well-being, or personality (range r = 0.11–0.48).


The Reserve-Building Measure provides a measure of activities and person-factors related to reserve that may potentially be useful in prospective research.


Reserve Measurement Psychometrics Activities Person characteristics Personality Quality of life Well-being 



We are grateful to Maria Orlando Edelen, Ph.D., Brian C. Healy, Ph.D., Adri van der Wurff, Ph.D., and David Eton, Ph.D. for helpful discussions; Randi Andenaes, RN, Ph.D., Inger Utne, RN, Ph.D., Nina Misvaer, RN, PHN, and other faculty from the Oslo and Akershus University College in Oslo, Norway, and Pythia Nieuwkerk, Ph.D., from the Academic Medical Center, University of Amsterdam, for help translating, piloting the measure, and suggesting changes to ensure its cross-cultural applicability. We gratefully acknowledge Victoria Powell, M.P.H., for assistance with data management and statistical programming early in the course of this study. Drs Sprangers and Nieuwkerk were supported by a grant from the Netherlands Organization for Scientific Research (NWO 310-20-003).

How to Obtain the Reserve-Building Measure

The interested reader can obtain the DeltaQuest Reserve-Building Measure and further information about item parameters by contacting the first author (CES) and licensing the tool from DeltaQuest Foundation for a specified use and term. License fees vary, depending on the nature of the licensee organization (e.g., academic, not-for-profit, for-profit). Such fees are used to fund further measurement development by DeltaQuest Foundation for use in clinical research and practice.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no potential conflicts of interest.


  1. 1.
    Bonanno, G. A., & Diminich, E. D. (2013). Annual research review: Positive adjustment to adversity–trajectories of minimal–impact resilience and emergent resilience. Journal of Child Psychology and Psychiatry, 54(4), 378–401.CrossRefPubMedGoogle Scholar
  2. 2.
    Bonanno, G. A., Kennedy, P., Galatzer-Levy, I. R., Lude, P., & Elfström, M. L. (2012). Trajectories of resilience, depression, and anxiety following spinal cord injury. Rehabilitation Psychology, 57(3), 236.CrossRefPubMedGoogle Scholar
  3. 3.
    Stern, Y. (2007). Cognitive reserve: Theory and applications (p. 344). New York: Taylor & Francis.Google Scholar
  4. 4.
    Schwartz, C. E., Rapkin, B. D., & Healy, B. C. (2016). Reserve and reserve-building activities research: Key challenges and future directions. BMC Neuroscience, 17, 62.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Schwartz, C. E., Snook, E. M., Quaranto, B. R., Benedict, R. H., & Vollmer, T. (2013). Cognitive reserve and patient-reported outcomes. Multiple Sclerosis Journal, 19(1), 87–105.CrossRefPubMedGoogle Scholar
  6. 6.
    Sumowski, J. F., Wylie, G. R., Chiaravalloti, N., & DeLuca, J. (2010). Intellectual enrichment lessens the effect of brain atrophy on learning and memory in multiple sclerosis. Neurology, 74(24), 1942–1945.CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Stern, Y., Gurland, B., Tatemichi, T. K., Tang, M. X., Wilder, D., & Mayeux, R. (1994). Influence of education and occupation on the incidence of Alzheimer’s disease. Journal of the American Medical Association, 271(13), 1004–1010.CrossRefPubMedGoogle Scholar
  8. 8.
    Benedict, R. H., Morrow, S. A., Weinstock Guttman, B., Cookfair, D., & Schretlen, D. J. (2010). Cognitive reserve moderates decline in information processing speed in multiple sclerosis patients. Journal of the International Neuropsychological Society, 16(5), 829–835.CrossRefPubMedGoogle Scholar
  9. 9.
    Sumowski, J. F., Rocca, M. A., Leavitt, V. M., Dackovic, J., Mesaros, S., Drulovic, J., et al. (2014). Brain reserve and cognitive reserve protect against cognitive decline over 4.5 years in MS. Neurology, 82(20), 1776–1783.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Sumowski, J. F., Wylie, G. R., Gonnella, A., Chiaravalloti, N., & Deluca, J. (2010). Premorbid cognitive leisure independently contributes to cognitive reserve in multiple sclerosis. Neurology, 75(16), 1428–1431.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448–460.CrossRefPubMedGoogle Scholar
  12. 12.
    Sumowski, J. F., Rocca, M. A., Leavitt, V. M., Riccitelli, G., Comi, G., Deluca, J., et al. (2013). Brain reserve and cognitive reserve in multiple sclerosis: What you’ve got and how you use it. Neurology, 80(24), 2186–2193.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Stern, Y., Habeck, C., Moeller, J., Scarmeas, N., Anderson, K. E., Hilton, H. J., et al. (2005). Brain networks associated with cognitive reserve in healthy young and old adults. Cerebral Cortex, 15(4), 394–402.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Stern, Y. (2006). Cognitive reserve and Alzheimer disease. Alzheimer Disease and Associated Disorders, 20(2), 112–117.CrossRefPubMedGoogle Scholar
  15. 15.
    Sumowski, J. F., & Leavitt, V. M. (2013). Cognitive reserve in multiple sclerosis. Mult Scler., 19(9), 1122–1127.CrossRefPubMedGoogle Scholar
  16. 16.
    Goleman, D. (2006). Emotional intelligence: Bantam.Google Scholar
  17. 17.
    Sole-Padulles, C., Bartres-Faz, D., Junque, C., Vendrell, P., Rami, L., Clemente, I. C., et al. (2009). Brain structure and function related to cognitive reserve variables in normal aging, mild cognitive impairment and Alzheimer’s disease. Neurobiology of Aging, 30(7), 1114–1124.CrossRefPubMedGoogle Scholar
  18. 18.
    Godin, G., & Shephard, R. (1997). Godin leisure-time exercise questionnaire. Medicine and Science in Sports and Exercise, 29(6), 36–38.Google Scholar
  19. 19.
    Development NCfON. O*NET Online.
  20. 20.
    Schwartz, C. E., Quaranto, B. R., Healy, B. C., Benedict, R. H., & Vollmer, T. L. (2013). Cognitive reserve and symptom experience in multiple sclerosis: A buffer to disability progression over time? Archives of Physical Medicine and Rehabilitation, 94(10), 1971–1981.CrossRefPubMedGoogle Scholar
  21. 21.
    Schwartz, C. E., Snook, E., Quaranto, B., Benedict, R. H., Rapkin, B. D., & Vollmer, T. (2013). Cognitive reserve and appraisal in multiple sclerosis. Multiple Sclerosis and Related Disorders, 2(1), 36–44.CrossRefPubMedGoogle Scholar
  22. 22.
    Schwartz, C. E., Ayandeh, A., Rodgers, J., Duberstein, P., Weinstock-Guttman, B., & Benedict, R. H. (2015). A new perspective on proxy report: Investigating implicit processes of understanding through patient-proxy congruence. Quality of Life Research, 24(11), 2637–2649.CrossRefPubMedGoogle Scholar
  23. 23.
    Roy, S., Schwartz, C. E., Duberstein, P., Dwyer, M. G., Zivadinov, R., Bergsland, N., et al. (2016). Synergistic effects of reserve and adaptive personality in multiple sclerosis. Journal of the International Neuropsychological Society., 22, 1–8.CrossRefGoogle Scholar
  24. 24.
    Schwartz, C. E., Quaranto, B. R., Healy, B. C., Benedict, R. H., & Vollmer, T. L. (2013). Altruism and health outcomes in multiple sclerosis: The effect of cognitive reserve. The Journal of Positive Psychology, 8(2), 144–152.CrossRefGoogle Scholar
  25. 25.
    Sherbourne, C. D., & Stewart, A. L. (1991). The MOS social support survey. Social Science and Medicine, 32(6), 705–714.CrossRefPubMedGoogle Scholar
  26. 26.
    Lubben, J. E. (1988). Assessing social networks among elderly populations. Family & Community Health, 11(3), 42–52.CrossRefGoogle Scholar
  27. 27.
    Schwartz, C. E., Powell, V. E., Edelen, M. O., Michael, W. (2016). Validating a patient-reported measure of reserve-building activities. Quality of Life Research, 25, 171.Google Scholar
  28. 28.
    Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). Hoboken, NJ: Wiley.Google Scholar
  29. 29.
    Hanmer, J., Cherepanov, D. (2015). A single question about a respondent’s perceived financial ability to pay monthly bills explains more variance in health utility scores than absolute income and assets questions. Quality of Life Research. 1–5.Google Scholar
  30. 30.
    Sangha, O., Stucki, G., Liang, M. H., Fossel, A. H., & Katz, J. N. (2003). The self-administered comorbidity questionnaire: A new method to assess comorbidity for clinical and health services research. Arthritis Care & Research, 49(2), 156–163.CrossRefGoogle Scholar
  31. 31.
    WHO. (2004). International statistical classification of diseases and health related problems (The) ICD-10. Geneva: World Health Organization.Google Scholar
  32. 32.
    Hays, R. D., Bjorner, J. B., Revicki, D. A., Spritzer, K. L., & Cella, D. (2009). Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Quality of Life Research, 18(7), 873–880.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    National Institute of Neurological Disorders and Stroke (2010). User manual for the quality of life in neurological disorders (Neuro-QOL) measures, version 1.0.Google Scholar
  34. 34.
    Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57, 1069–1081.CrossRefGoogle Scholar
  35. 35.
    Rammstedt, B., & John, O. P. (2007). Measuring personality in one minute or less: A 10-item short version of the Big Five Inventory in English and German. Journal of Research in Personality, 41(1), 203–212.CrossRefGoogle Scholar
  36. 36.
    Muthen, B., & Muthen, L. (1998). Mplus User’s Guide. Los Angeles: Muthen & Muthen.Google Scholar
  37. 37.
    Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.CrossRefGoogle Scholar
  38. 38.
    Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Abingdon: Routledge.Google Scholar
  39. 39.
    Samejima, F. (2016). Graded response models. Handbook of item response theory (pp. 95–107). Boca Raton: CRC Press.Google Scholar
  40. 40.
    Cai, L., Du Toit, S., & Thissen, D. (2011). IRTPRO: Flexible, multidimensional, multiple categorical IRT modeling [Computer software]. Chicago, IL: Scientific Software International.Google Scholar
  41. 41.
    Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
  42. 42.
    Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.CrossRefPubMedGoogle Scholar
  43. 43.
    StataCorp. (2016). Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.Google Scholar
  44. 44.
    Scarmeas, N., Levy, G., Tang, M. X., Manly, J., & Stern, Y. (2001). Influence of leisure activity on the incidence of Alzheimer’s disease. Neurology, 57(12), 2236–2242.CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Lindstrom, H. A., Fritsch, T., Petot, G., Smyth, K. A., Chen, C. H., Debanne, S. M., et al. (2005). The relationships between television viewing in midlife and the development of Alzheimer’s disease in a case–control study. Brain and Cognition, 58(2), 157–165.CrossRefPubMedGoogle Scholar
  46. 46.
    Huber, M., Knottnerus, J. A., Green, L., van der Horst, H., Jadad, A. R., Kromhout, D., et al. (2011). How should we define health? British Medical Journal, 343, d4163.CrossRefPubMedGoogle Scholar
  47. 47.
    Schwartz, C. E., & Daltroy, L. H. (1999). Learning from unreliability: The importance of inconsistency in coping dynamics. Social Science and Medicine, 48(5), 619–631.CrossRefPubMedGoogle Scholar
  48. 48.
    Richards, M., & Deary, I. J. (2005). A life course approach to cognitive reserve: A model for cognitive aging and development? Annals of Neurology, 58, 612–622.CrossRefGoogle Scholar
  49. 49.
    Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.CrossRefGoogle Scholar
  50. 50.
    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Carolyn E. Schwartz
    • 1
    • 2
    Email author
  • Wesley Michael
    • 3
  • Jie Zhang
    • 1
  • Bruce D. Rapkin
    • 4
  • Mirjam A. G. Sprangers
    • 5
  1. 1.DeltaQuest Foundation, IncConcordUSA
  2. 2.Departments of Medicine and Orthopaedic SurgeryTufts University Medical SchoolBostonUSA
  3. 3.Rare Patient Voice, LLCTowsonUSA
  4. 4.Division of Community Collaboration & Implementation Science, Department of Epidemiology and Population HealthAlbert Einstein College of MedicineBronxUSA
  5. 5.Department of Medical Psychology, Academic Medical CenterUniversity of AmsterdamAmsterdamThe Netherlands

Personalised recommendations