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The Patient Activation Measure: a validation study in a neurological population

Abstract

Purpose

To assess the validity of the Patient Activation Measure (PAM13) of patient activation in persons with neurological conditions.

Methods

“The Everyday Experience of Living with and Managing a Neurological Condition” (The LINC study) surveyed 948 adults with neurological conditions residing in Canada in 2011 and 2012. Using data for 722 respondents who met coding requirements for the PAM-13, we examined the properties of the measure using principle components analysis, inter-item correlations and Cronbach’s alpha to assess unidimensionality and internal consistency. Rasch modeling was used to assess item performance and scaling. Construct validity was assessed by calculating associations between the PAM and known correlates.

Results

PAM-13 provides a suitably reliable and valid instrument for research in patients with neurological conditions, but scaling problems may yield measurement error and biases for those with low levels of activation. This is of particular importance when used in clinical settings or for individual client care. Our study also suggests that measurement of activation may benefit from tailoring items and scaling to specific diagnostic groups such as people with neurological conditions, thus allowing the PAM-13 to recognize unique attributes and management challenges in those conditions.

Conclusions

The PAM-13 is an internally reliable and valid tool for research purposes. The use of categorical activation “level” in clinical settings should be done with caution.

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References

  1. 1.

    Hibbard, J. H., & Greene, J. (2013). What the evidence shows about patient activation: Better health outcomes and care experiences; fewer data on costs. Health Affairs (Millwood), 32(2), 207–214.

    Article  Google Scholar 

  2. 2.

    Wagner, E. H. (1998). Chronic disease management: What will it take to improve care for chronic illness? Effective clinical practice, 1(1), 2–4.

    CAS  PubMed  Google Scholar 

  3. 3.

    Wagner, E. E. H. (2001). Meeting the needs of chronically ill people. British Medical Journal, 323(7319), 945–946.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  4. 4.

    Barr, V. J., Robinson, S., Marin-Link, B., Underhill, L., Dotts, A., Ravensdale, D., et al. (2003). The expanded chronic care model: An integration of concepts and strategies from population health promotion and the chronic care model. Hospital Quarterly, 7(1), 73–82.

    PubMed  Google Scholar 

  5. 5.

    Greene, J., & Hibbard, J. H. (2012). Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. Journal of General Internal Medicine, 27(5), 520–526.

    PubMed Central  PubMed  Article  Google Scholar 

  6. 6.

    Stepleman, L., Rutter, M., Hibbard, J., Johns, L., Wright, D., & Hughes, M. (2010). Validation of the patient activation measure in a multiple sclerosis clinic sample and implications for care. Disability and Rehabilitation, 32(19), 1558–1567.

    PubMed  Article  Google Scholar 

  7. 7.

    Fowles, J. B., Terry, P., Xi, M., Hibbard, J., Bloom, C. T., & Harvey, L. (2009). Measuring self-management of patients’ and employees’ health: Further validation of the patient activation measure (PAM) based on its relation to employee characteristics. Patient Education and Counseling, 77(1), 116–122.

    PubMed  Article  Google Scholar 

  8. 8.

    Hibbard, J. H., Collins, P. A., Mahoney, E., & Baker, L. H. (2010). The development and testing of a measure assessing clinician beliefs about patient self-management. Health Expectations, 13(1), 65–72.

    PubMed  Article  Google Scholar 

  9. 9.

    Hibbard, J. H., Mahoney, E. R., Stockard, J., & Tusler, M. (2005). Development and testing of a short form of the patient activation measure. Health Services Research, 40(6 Pt 1), 1918–1930.

    PubMed Central  PubMed  Article  Google Scholar 

  10. 10.

    Hibbard, J. H., Mahoney, E. R., Stock, R., & Tusler, M. (2007). Do increases in patient activation result in improved self-management behaviors? Health Services Research, 42(4), 1443–1463.

    PubMed Central  PubMed  Article  Google Scholar 

  11. 11.

    Kaplan, R. M., Anderson, J. P., Wu, A. W., Mathews, W. C., Kozin, F., & Orenstein, D. (1989). The quality of well-being scale. Applications in AIDS, cystic fibrosis, and arthritis. Medical Care, 27(3 Suppl.), 27–43.

    Article  Google Scholar 

  12. 12.

    Alexander, J. A., Hearld, L. R., Mittler, J. N., & Harvey, J. (2012). Patient–physician role relationships and patient activation among individuals with chronic illness. Health Services Research, 47(3 Pt 1), 1201–1223.

    PubMed Central  PubMed  Article  Google Scholar 

  13. 13.

    Glasgow, R. E., Toobert, D. J., Hampson, S. E., & Strycker, L. A. (2002). Implementation, generalization and long-term results of the “choosing well” diabetes self-management intervention. Patient Education Counseling, 48(2), 115–122.

    PubMed  Article  Google Scholar 

  14. 14.

    Begum, N., Donald, M., Ozolins, I. Z., & Dower, J. (2011). Hospital admissions, emergency department utilisation and patient activation for self-management among people with diabetes. Diabetes Research and Clinical Practice, 93(2), 260–267.

    PubMed  Article  Google Scholar 

  15. 15.

    Hibbard, J. H., & Cunningham, P. J. (2008). How engaged are consumers in their health and health care, and why does it matter? Res Briefs, 8, 1–9.

    Google Scholar 

  16. 16.

    Hibbard, J. H., Stockard, J., Mahoney, E. R., & Tusler, M. (2004). Development of the patient activation measure (PAM): Conceptualizing and measuring activation in patients and consumers. Health Services Research, 39(4 Pt 1), 1005–1026.

    PubMed Central  PubMed  Article  Google Scholar 

  17. 17.

    Insignia Health. (2011). Patient activation measure (PAM) 13™ License Materials copyright Insignia Health, LLC.

  18. 18.

    Brenk-Franz, K., Hibbard, J. H., Herrmann, W. J., Freund, T., Szecsenyi, J., Djalali, S., et al. (2013). Validation of the German version of the patient activation measure 13 (PAM13-D) in an international multicentre study of primary care patients. PLoS One, 8(9), e74786.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  19. 19.

    Zill, J. M., Dwinger, S., Kriston, L., Rohenkohl, A., Harter, M., & Dirmaier, J. (2013). Psychometric evaluation of the German version of the patient activation measure (PAM13). BMC Public Health, 13, 1027-2458-13-1027.

    Article  Google Scholar 

  20. 20.

    Maindal, H. T., Sandbaek, A., Kirkevold, M., & Lauritzen, T. (2011). Effect on motivation, perceived competence, and activation after participation in the “Ready to Act” programme for people with screen-detected dysglycaemia: A 1-year randomised controlled trial, Addition-DK. Scandinavian Journal of Public Health, 39(3), 262–271.

    PubMed  Article  Google Scholar 

  21. 21.

    Rademakers, J., Nijman, J., van der Hoek, L., Heijmans, M., & Rijken, M. (2012). Measuring patient activation in The Netherlands: Translation and validation of the American short form patient activation measure (PAM13). BMC Public Health, 12, 577.

    PubMed Central  PubMed  Article  Google Scholar 

  22. 22.

    Green, C. A., Perrin, N. A., Polen, M. R., Leo, M. C., Hibbard, J. H., & Tusler, M. (2010). Development of the patient activation measure for mental health. Administration and Policy in Mental Health, 37(4), 327–333.

    PubMed Central  PubMed  Article  Google Scholar 

  23. 23.

    Skolasky, R. L., MacKenzie, E. J., Riley, L. H, I. I. I., & Wegener, S. T. (2009). Psychometric properties of the patient activation measure among individuals presenting for elective lumbar spine surgery. Quality of Life Research, 18(10), 1357–1366.

    PubMed Central  PubMed  Article  Google Scholar 

  24. 24.

    Skolasky, R. L., Green, A. F., Scharfstein, D., Boult, C., Reider, L., & Wegener, S. T. (2011). Psychometric properties of the patient activation measure among multimorbid older adults. Health Services Research, 46(2), 457–478.

    PubMed Central  PubMed  Article  Google Scholar 

  25. 25.

    Hung, M., Carter, M., Hayden, C., Dzierzon, R., Morales, J., Snow, L., et al. (2013). Psychometric assessment of the patient activation measure short form (PAM-13) in rural settings. Quality of Life Research, 22(3), 521–529.

    PubMed  Article  Google Scholar 

  26. 26.

    Cook, D. A., & Beckman, T. J. (2006). Current concepts in validity and reliability for psychometric instruments: Theory and application. The American Journal of Medicine, 119(2), 166.e7-166.16.

    Article  Google Scholar 

  27. 27.

    Malcomson, K. S., Lowe-strong, A. S., & Dunwoody, L. (2008). What can we learn from the personal insights of individuals living and coping with multiple sclerosis? Disability and Rehabilitation, 30(9), 662–674.

    CAS  PubMed  Article  Google Scholar 

  28. 28.

    Versnel, J., Packer, T., Weeks, L. E., Brown, J., Godwin, M., Hutchinson, S., et al. (2013). The everyday experience of living with and managing a neurological condition (the LINC study): Study design. BMC Neurology, 13, 30-2377-13-30.

    Article  Google Scholar 

  29. 29.

    Caesar-Chavannes, C. R., & MacDonald, S. (2013). Cross-Canada forum—National Population Health Study of neurological conditions in Canada. Chronic Diseases Injuries in Canada, 33(3), 188–191.

    CAS  PubMed  Google Scholar 

  30. 30.

    Statistics Canada. (2009). User guide 2007–2008 microdata files. Canadian Community Health Survey (CCHS)—Annual Component. Ottawa: Statistics Canada.

  31. 31.

    Harvey, L., Fowles, J. B., Xi, M., & Terry, P. (2012). When activation changes, what else changes? The relationship between change in patient activation measure (PAM) and employees’ health status and health behaviors. Patient Education and Counseling, 88(2), 338–343.

    PubMed  Article  Google Scholar 

  32. 32.

    Hawthorne, G., Osborne, R. H., Taylor, A., & Sansoni, J. (2007). The SF36 version 2: Critical analyses of population weights, scoring algorithms and population norms. Quality of Life Research, 16(4), 661–673.

    PubMed  Article  Google Scholar 

  33. 33.

    Guilfoyle, M. R., Seeley, H. M., Corteen, E., Harkin, C., Richards, H., Menon, D. K., et al. (2010). Assessing quality of life after traumatic brain injury: Examination of the short form 36 health survey. Journal of Neurotrauma, 27(12), 2173–2181.

    PubMed  Article  Google Scholar 

  34. 34.

    Jenkinson, C., Hobart, J., Chandola, T., Fitzpatrick, R., Peto, V., Swash, M., et al. (2002). Use of the short form health survey (SF-36) in patients with amyotrophic lateral sclerosis: Tests of data quality, score reliability, response rate and scaling assumptions. Journal of Neurology, 249(2), 178–183.

    PubMed  Article  Google Scholar 

  35. 35.

    Marra, C. A., Woolcott, J. C., Kopec, J. A., Shojania, K., Offer, R., Brazier, J. E., et al. (2005). A comparison of generic, indirect utility measures (the HUI2, HUI3, SF-6D, and the EQ-5D) and disease-specific instruments (the RAQoL and the HAQ) in rheumatoid arthritis. Social Science and Medicine, 60(7), 1571–1582.

    PubMed  Article  Google Scholar 

  36. 36.

    Feng, Y., Bernier, J., McIntosh, C., & Orpana, H. (2009). Validation of disability categories derived from Health Utilities Index Mark 3 scores. Health Reports, 20(2), 43–50.

    PubMed  Google Scholar 

  37. 37.

    Godwin, M., Streight, S., Dyachuk, E., van den Hooven, E. C., Ploemacher, J., Seguin, R., et al. (2008). Testing the Simple Lifestyle Indicator Questionnaire: Initial psychometric study. Canadian Family Physician, 54(1), 76–77.

    PubMed Central  PubMed  Google Scholar 

  38. 38.

    R Development Core Team. (2006). R: A language and environment for statistical computing. Vienna: R Development Core Team.

    Google Scholar 

  39. 39.

    Mair, P., & Hatzinger, R. (2006). eRm; extended Rasch models. R package version 0.3.2. http://CRAN.R-project.org/. (Accessed October 2013).

  40. 40.

    Mair, P., & Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49(1), 26–43.

    Google Scholar 

  41. 41.

    Hattie, J. (1985). Methodology review: Assessing unidimensionality of tests and items. Applied Psychological Measurement, 9(2), 139–164.

    Article  Google Scholar 

  42. 42.

    Maindal, H. T., Sokolowski, I., & Vedsted, P. (2009). Translation, adaptation and validation of the American short form patient activation measure (PAM13) in a Danish version. BMC Public Health, 9, 209.

    PubMed Central  PubMed  Article  Google Scholar 

  43. 43.

    World Health Organization. (2003). Adherence to long-term therapies: Evidence for action (p. 12). Geneva: World Health Organization.

  44. 44.

    Remington, G., Rodriguez, Y., Logan, D., Williamson, C., & Treadaway, K. (2013). Facilitating medication adherence in patients with multiple sclerosis. International Journal of MS Care, 15(1), 36–45.

    PubMed Central  PubMed  Article  Google Scholar 

  45. 45.

    Grosset, D., Antonini, A., Canesi, M., Pezzoli, G., Lees, A., Shaw, K., et al. (2009). Adherence to antiparkinson medication in a multicenter European study. Movement Disorders, 24(6), 826–832.

    PubMed  Article  Google Scholar 

  46. 46.

    Drennan, J. (2003). Cognitive interviewing: Verbal data in the design and pretesting of questionnaires. Journal of Advanced Nursing, 42(1), 57–63.

    PubMed  Article  Google Scholar 

  47. 47.

    Ghahari, S., Forwell, S., & Khoshbin, L. (2014). The multiple sclerosis self-management scale: Clinicometric testing. International Journal of MS Care,. doi:10.7224/1537-2073.2013-019.

    PubMed Central  PubMed  Google Scholar 

  48. 48.

    Harvey, L., Fowles, J. B., Xi, M., & Terry, P. (2012). When activation changes, what else changes? The relationship between change in patient activation measure (PAM) and employees’ health status and health behaviors. Patient Education and Counseling, 88(2), 338–343.

    PubMed  Article  Google Scholar 

  49. 49.

    Mosen, D. M., Schmittdiel, J., Hibbard, J., Sobel, D., Remmers, C., & Bellows, J. (2007). Is patient activation associated with outcomes of care for adults with chronic conditions? Journal of Ambulatory Care Management, 30(1), 21–29.

    PubMed  Article  Google Scholar 

  50. 50.

    Ledford, C. J. W., Ledford, C. C., & Childress, M. A. (2013). Exploring patient activation in the clinic: Measurement from three perspectives. Health Education and Behavior, 40(3), 339–345.

    PubMed  Article  Google Scholar 

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Acknowledgments

This study was part of the National Population Health Study of Neurological Conditions. We wish to acknowledge the membership of Neurological Health Charities Canada and the Public Health Agency of Canada for their contribution to the success of this initiative. Funding for the study was provided by the Public Health Agency of Canada. The opinions expressed in this publication are those of the authors/researchers and do not necessarily reflect the official views of the Public Health Agency of Canada. The authors wish to thank the many participants in the LINC study as well as the large research team who made the study possible.

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Correspondence to Tanya L. Packer.

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Packer, T.L., Kephart, G., Ghahari, S. et al. The Patient Activation Measure: a validation study in a neurological population. Qual Life Res 24, 1587–1596 (2015). https://doi.org/10.1007/s11136-014-0908-0

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Keywords

  • Chronic disease management
  • Measurement
  • Validation
  • Neurological conditions
  • Patient activation
  • PAM-13