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Measurement of stable changes of self-management skills after rehabilitation: a latent state–trait analysis of the Health Education Impact Questionnaire (heiQ™)

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Abstract

Purpose

To assess stable effects of self-management programs, measurement instruments should primarily capture the attributes of interest, for example, the self-management skills of the measured persons. However, measurements of psychological constructs are always influenced by both aspects of the situation (states) and aspects of the person (traits). This study tests whether the Health Education Impact Questionnaire (heiQ™), an instrument assessing a wide range of proximal outcomes of self-management programs, is primarily influenced by person factors instead of situational factors. Furthermore, measurement invariance over time, changes in traits and predictors of change for each heiQ™ scale were examined.

Methods

Subjects were N = 580 patients with rheumatism, asthma, orthopedic conditions or inflammatory bowel disease, who filled out the heiQ™ at the beginning, the end of and 3 months after a disease-specific inpatient rehabilitation program in Germany. Structural equation modeling techniques were used to estimate latent trait-change models and test for measurement invariance in each heiQ™ scale. Coefficients of consistency, occasion specificity and reliability were computed.

Results

All scales showed scalar invariance over time. Reliability coefficients were high (0.80–0.94), and consistency coefficients (0.49–0.79) were always substantially higher than occasion specificity coefficients (0.14–0.38), indicating that the heiQ™ scales primarily capture person factors. Trait-changes with small to medium effect sizes were shown in five scales and were affected by sex, age and diagnostic group.

Conclusion

The heiQ™ can be used to assess stable effects in important outcomes of self-management programs over time, e.g., changes in self-management skills or emotional well-being.

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References

  1. Lorig, K. R. (2003). Self-management education: More than a nice extra. Medical Care, 41(6), 699–701.

    PubMed  Google Scholar 

  2. Lorig, K. R., & Holman, H. (2003). Self-management education: History, definition, outcomes, and mechanisms. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine, 26(1), 1–7.

    Article  Google Scholar 

  3. Osborne, R. H., Spinks, J. M., & Wicks, I. P. (2004). Patient education and self-management programs in arthritis. Medical Journal of Australia, 180(5 Suppl), S23–S26.

    PubMed  Google Scholar 

  4. Faller, H., Reusch, A., & Meng, K. (2011). DGRW-Update: Patientenschulung. Rehabilitation, 50(5), 284–291.

    Article  PubMed  CAS  Google Scholar 

  5. Steyer, R., Schmitt, M., & Eid, M. (1999). Latent state–trait theory and research in personality and individual differences. European Journal of Personality, 13(5, Spec Issue), 389–408.

    Article  Google Scholar 

  6. Nesselroade, J. R. (2004). Intraindividual variability and short-term change. Gerontology, 50(1), 44–47.

    Article  PubMed  Google Scholar 

  7. Eid, M. (1995). Modelle der Messung von Personen in Situationen. Weinheim: Psychologie Verlags Union.

    Google Scholar 

  8. Steyer, R., Ferring, D., & Schmitt, M. J. (1992). States and traits in psychological assessment. European Journal of Psychological Assessment, 8(2), 79–98.

    Google Scholar 

  9. Steyer, R., Geiser, C., & Fiege, C. (2012). Latent state–trait models. In H. Cooper, P. M. Camic, D. L. Long, A. T. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology (Vol. 3, pp. 291–308)., Data analysis and research publication Washington, DC: American Psychological Association.

    Google Scholar 

  10. Geiser, C., & Lockhart, G. (2012). A comparison of four approaches to account for method effects in latent state–trait analyses. Psychological Methods, 17(2), 255–283.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Courvoisier, D. S., Agoritsas, T., Glauser, J., Michaud, K., Wolfe, F., Cantoni, E., et al. (2012). Pain as an important predictor of psychosocial health in patients with rheumatoid arthritis. Arthritis Care & Research, 64(2), 190–196.

    Article  Google Scholar 

  12. Courvoisier, D. S., Eid, M., & Nussbeck, F. W. (2007). Mixture distribution latent state–trait analysis: Basic ideas and applications. Psychological Methods, 12(1), 80–104.

    Article  PubMed  Google Scholar 

  13. Eid, M., & Hoffmann, L. (1998). Measuring variability and change with an item response model for polytomous variables. Journal of Educational and Behavioral Statistics, 23(3), 193–215.

    Article  Google Scholar 

  14. Steyer, R., Krambeer, S., & Hannöver, W. (2004). Modeling latent trait-change. In K. Van Montfort, H. Oud, & A. Satorra (Eds.), Recent developments on structural equation modeling: Theory and applications (pp. 337–357). Amsterdam: Kluwer Academic Press.

    Chapter  Google Scholar 

  15. Osborne, R. H., Elsworth, G. R., & Whitfield, K. (2007). The Health Education Impact Questionnaire (heiQ): An outcomes and evaluation measure for patient education and self-management interventions for people with chronic conditions. Patient Education and Counseling, 66(2), 192–201.

    Article  PubMed  Google Scholar 

  16. Osborne, R. H., Batterham, R., & Livingston, J. (2011). The evaluation of chronic disease self-management support across settings: The international experience of the health education impact questionnaire quality monitoring system. The Nursing clinics of North America, 46(3), 255–270.

    Article  PubMed  Google Scholar 

  17. Epstein, J., Osborne, R. H., Elsworth, G. R., Beaton, D. E., & Guillemin, F. (2013). Cross-cultural adaptation of the Health Education Impact Questionnaire: Experimental study showed expert committee, not back-translation, added value. Journal of Clinical Epidemiology. doi: 10.1016/j.jclinepi.2013.07.013

  18. Schuler, M., Musekamp, G., Faller, H., Ehlebracht-Konig, I., Gutenbrunner, C., Kirchhof, R., et al. (2013). Assessment of proximal outcomes of self-management programs: Translation and psychometric evaluation of a German version of the Health Education Impact Questionnaire (heiQ). Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 22(6), 1391–1403.

    Article  Google Scholar 

  19. Ehlebracht-König, I., & Bönisch, A. (2007). Beispiel einer qualitätsgesicherten Schulung bei Patienten mit Spondylitis ankylosans. Praxis Klinische Verhaltensmedizin und Rehabilitation, 75, 15–20.

    Google Scholar 

  20. Ehlebracht-König, I., Bönisch, A., & Pönicke, J. (2009). Fraktionierte rehabilitation: Ergebnisse einer randomisierten, kontrollierten Studie. Rehabilitation, 48, 30–38.

    Article  PubMed  Google Scholar 

  21. Schultz, K., Petro, W., Müller, C., & Schwiersch, M. (2000). Asthma-Verhaltenstraining mit Erwachsenen: Konzepte und Materialien. In F. Petermann & P. Warschburger (Eds.), Asthma bronchiale (pp. 275–294). Göttingen: Hogrefe.

    Google Scholar 

  22. Schultz, K., Schwiersch, M., Petro, W., Mühlig, S., & Petermann, F. (2000). Individualisiertes, modular strukturiertes Patientenverhaltenstraining bei obstruktiven Atemwegserkrankungen in der stationären Rehabilitation. Pneumologie, 54, 296–305.

    Article  PubMed  CAS  Google Scholar 

  23. Deutsche Rentenversicherung Bund. (2011). Reha Therapiestandards Chronischer Rückenschmerz. Berlin: Deutsche Rentenversicherung Bund.

    Google Scholar 

  24. Widaman, K. F., Ferrer, E., & Conger, R. D. (2010). Factorial invariance within longitudinal structural equation models: Measuring the same construct across time. Child Development Perspectives, 4(1), 10–18.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Jelitte, M., & Schuler, M. (2012). Messen wir immer das Gleiche? Zur Invarianz von Messungen und Response-Shift in der Rehabilitation - Teil 2. Die Rehabilitation, 51(6), 415–423.

    Article  PubMed  CAS  Google Scholar 

  26. Meredith, W., & Horn, J. (2001). The role of factorial invariance in modeling growth and change. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change (pp. 203–240). Washington, DC: American Psychological Association.

    Chapter  Google Scholar 

  27. Schuler, M., & Jelitte, M. (2012). Messen wir bei allen Personen das Gleiche? Zur Invarianz von Messungen und Response Shift in der Rehabilitation - Teil 1. Die Rehabilitation, 51(5), 332–339.

    Article  PubMed  CAS  Google Scholar 

  28. Geiser, C., Eid, M., West, S. G., Lischetzke, T., & Nussbeck, F. W. (2012). A comparison of method effects in two confirmatory factor models for structurally different methods. Structural Equation Modeling, 19(3), 409–436.

    Article  Google Scholar 

  29. Eid, M. (2000). A multitrait-multimethod model with minimal assumptions. Psychometrika, 65(2), 241–261.

    Article  Google Scholar 

  30. Yoon, M., & Millsap, R. E. (2007). Detecting violations of factorial invariance using data-based specification searches: A Monte Carlo study. Structural Equation Modeling, 14(3), 453–463.

  31. Oberski, D. J. (2009). Jrule for Mplus (Version 0.91). http://wiki.github.com/daob/JruleMplus/.

  32. Steinmetz, H. (2013). Analyzing observed composite differences across groups is partial measurement invariance enough? Methodology-European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 1–12.

    Article  Google Scholar 

  33. Saris, W. E., Satorra, A., & van der Veld, W. M. (2009). Testing structural equation models or detection of misspecifications? Structural Equation Modeling, 16(4), 561–582.

    Article  Google Scholar 

  34. van der Veld, W. M., & Saris, W. E. (2011). Causes of generalized social trust. In E. Davidov, P. Schmidt, & J. Billiet (Eds.), European association for methodology series (pp. 207–247). New York, NY: Routledge/Taylor & Francis Group.

    Google Scholar 

  35. Byrne, B. M., Shavelson, R. J., & Muthen, B. (1989). Testing for the equivalence of factor covariance and mean structures—The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456–466.

    Article  Google Scholar 

  36. Steyer, R., Eid, M., & Schwenkmezger, P. (1997). Modeling true intraindividual change: True change as a latent variable. Methods of Psychological Research, 2(1), 21–33.

    Google Scholar 

  37. Leonhart, R. (2004). Effektgrößenberechnung bei Interventionsstudien. Die Rehabilitation, 43(4), 241–246.

    Article  PubMed  CAS  Google Scholar 

  38. Kazis, L. E., Anderson, J. J., & Meenan, R. F. (1989). Effect sizes for interpreting changes in health status. Medical Care, 27(3 Suppl), S178–S189.

    Article  PubMed  CAS  Google Scholar 

  39. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2., 2 print. ed.). Hillsdale, NJ u.a.: Erlbaum.

  40. West, S. G., Aiken, L. S., & Krull, J. L. (1996). Experimental personality designs: Analyzing categorical by continuous variable interactions. Journal of Personality, 64(1), 1–48.

    Article  PubMed  CAS  Google Scholar 

  41. Eid, M., & Diener, E. (2004). Global judgments of subjective well-being: Situational variability and long-term stability. Social Indicators Research, 65(3), 245–277.

    Article  Google Scholar 

  42. Eid, M., & Diener, E. (1999). Intraindividual variability in affect: Reliability, validity, and personality correlates. Journal of Personality and Social Psychology, 76(4), 662–676.

    Article  Google Scholar 

  43. Muthén, L. K., & Muthén, B. (2010). Mplus user;s guide. Los Angeles: Muthén & Muthén.

    Google Scholar 

  44. Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

    Article  Google Scholar 

  45. Chen, F., Bollen, K. A., Paxton, P., Curran, P. J., & Kirby, J. B. (2001). Improper solutions in structural equation models: Causes, consequences, and strategies. Sociological Methods & Research, 29(4), 468–508.

    Article  Google Scholar 

  46. Mohiyeddini, C., Hautzinger, M., & Bauer, S. (2002). A latent state–trait analysis on assessing trait and state components of three instruments for measuring depression: ADS, BDI, and SDS. Diagnostica, 48(1), 12–18.

    Article  Google Scholar 

  47. Kolenikov, S., & Bollen, K. A. (2012). Testing negative error variances: Is a Heywood case a symptom of misspecification? Sociological Methods & Research, 41(1), 124–167.

    Article  Google Scholar 

  48. Muhlig, S., Schultz, K., de Vries, U., & Petermann, F. (2000). Grundlagen der Patientenschulung bei Asthma. In F. Petermann & P. Warschburger (Eds.), Asthma bronchiale (pp. Seiten 147–174). Gottingen: Hogrefe.

  49. Nolte, S., Elsworth, G. R., Sinclair, A. J., & Osborne, R. H. (2009). Tests of measurement invariance failed to support the application of the “then-test”. Journal of Clinical Epidemiology, 62(11), 1173–1180.

    Article  PubMed  Google Scholar 

  50. Oort, F. J. (2005). Using structural equation modeling to detect response shifts and true change. Quality of Life Research, 14(3), 587–598.

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors wish to thank our cooperation clinics: Rehabilitation Center Bad Eilsen, Hospital Bad Bramstedt, Hospital Bad Oexen, Hospital Bad Reichenhall, Hospital Norderney, Deegenberg Hospital Bad Kissingen and Rehabilitation Center Bad Mergentheim Hospital Taubertal. This project was funded by the German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung). Professor Osborne was supported in part by an Australian National Health and Medical Research Council Population Health Career Development Award (#400391).

Conflict of interest

The authors state that there are no conflicts of interests.

Author information

Authors and Affiliations

  1. Department of Medical Psychology, Medical Sociology, and Rehabilitation Sciences, University of Würzburg, Klinikstr. 3, 97070, Würzburg, Germany

    M. Schuler, G. Musekamp & H. Faller

  2. Department of Psychology, University of Freiburg, Freiburg, Germany

    J. Bengel

  3. Hospital for Rehabilitation Medicine, Medical School Hannover, Hannover, Germany

    M. Schwarze, K. Spanier & Chr. Gutenbrunner

  4. Rehabilitation Center Bad Eilsen, Bad Eilsen, Germany

    I. Ehlebracht-König

  5. Department of Psychosomatic Medicine, Medical Clinic, Charité – Universitätsmedizin Berlin, Berlin, Germany

    S. Nolte

  6. School of Health and Social Development, Population Health Strategic Research Centre, Deakin University, Melbourne, Australia

    S. Nolte & R. H. Osborne

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  1. M. Schuler
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  2. G. Musekamp
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Correspondence to M. Schuler.

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Schuler, M., Musekamp, G., Bengel, J. et al. Measurement of stable changes of self-management skills after rehabilitation: a latent state–trait analysis of the Health Education Impact Questionnaire (heiQ™). Qual Life Res 23, 2531–2543 (2014). https://doi.org/10.1007/s11136-014-0693-9

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