Quality of Life Research

, Volume 26, Issue 4, pp 1071–1080 | Cite as

Validation of the Patient Activation Measure (PAM-13) among adults with cardiac conditions in Singapore

  • Bi Xia Ngooi
  • Tanya L. Packer
  • George Kephart
  • Grace Warner
  • Karen Wei Ling Koh
  • Raymond Ching Chiew Wong
  • Serene Peiying Lim
Article

Abstract

Purpose

The Patient Activation Measure (PAM-13) measures patients’ knowledge, skill, and confidence in chronic condition self-management. The purpose of this study was to assess the validity of PAM-13 (English version) among English-speaking adults with cardiac conditions in Singapore.

Methods

A cross-sectional study was conducted in a convenient sample of 270 heart clinic patients. Using the unitary concept of validity, evidence of (1) internal structure via data quality, unidimensionality, differential item functioning, and internal consistency, (2) response process through item difficulty and item fit using Rasch modeling, and (3) relationship to other variables via correlations with depression and self-efficacy were examined.

Results

The item response was high with only one missing answer. All items had a small floor effect, but nine out of 13 items had a ceiling effect larger than 15 %. Cronbach’s α was 0.86, and average inter-item correlations was 0.324. Results suggested unidimensionality; however, differences in item difficulty ranking were found. A low, negative correlation was found with depression, while a moderate, positive correlation was found with self-efficacy.

Conclusion

Evidence in all three areas of validity were mixed. Caution should be exercised when using categorical activation “level” to inform clinical decisions.

Keywords

Patient Activation Measure Cardiac Singapore Chronic disease Self-management Validation 

References

  1. 1.
    Acock, A. C. (2008). A gentle introduction to STATA (2nd ed.). Texas: Stata Press.Google Scholar
  2. 2.
    Ahn, Y.-H., Yi, C.-H., Ham, O.-K., & Kim, B.-J. (2014). Psychometric properties of the Korean version of the “Patient Activation Measure 13” (PAM13-K) in patients with osteoarthritis. Evaluation and the Health Professions,. doi:10.1177/0163278714540915.PubMedGoogle Scholar
  3. 3.
    Alegria, M., Sribney, W., Perez, D., Laderman, M., & Keefe, K. (2009). The role of patient activation on patient-provider communication and quality of care for US and foreign born Latino patients. Journal of General Internal Medicine, 24, 534–541.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    American Educational Research Association (AERA), American Psychological Association (APA), National Council on Measurement in Education (NCME). (1999). Standards for education and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
  5. 5.
    Asudulv, A. (2013). The over time development of chronic illness self-management patterns: A longitudinal qualitative study. BMC Public Health, 13, 452–467.CrossRefGoogle Scholar
  6. 6.
    Baylor, C., Hula, W., Donovan, N. J., Doyle, P. J., Kendall, D., & Yorkston, K. (2011). An introduction to item response theory and Rasch models for speech-language pathologists. American Journal of Speech-Language Pathology, 20, 243–259.CrossRefPubMedGoogle Scholar
  7. 7.
    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, e74786. doi:10.1371/journal.pone.0074786.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model. Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  9. 9.
    Chen, W.-H., Lenderking, W., Jin, Y., Wyrwich, K. W., Gelhorn, H., & Revicki, D. A. (2014). Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank data. Quality of Life Research, 23, 485–493.CrossRefPubMedGoogle Scholar
  10. 10.
    Chong, S. A., Abdin, E., Vaingankar, J. A., Heng, D., Sherbourne, C., Yap, M., et al. (2012). A population-based survey of mental disorders in Singapore. ANNALS Academy of Medicine Singapore, 41, 49–66.Google Scholar
  11. 11.
    Cook, D. A., & Beckman, T. J. (2006). Current concepts in validity and reliability for psychometric instruments: Theory and application. The American Journal of Medicine, 199, 166.e7–166.e16.CrossRefGoogle Scholar
  12. 12.
    Fowles, J. B., Terry, P., Si, 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 & Counselling, 77, 116–122.CrossRefGoogle Scholar
  13. 13.
    Gardetto, N. J. (2011). Self-management in heart failure: Where have we been and where should we go? Journal of Multidisciplinary Healthcare, 4, 39–51.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    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, 327–333.CrossRefPubMedGoogle Scholar
  15. 15.
    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, 520–526.CrossRefPubMedGoogle Scholar
  16. 16.
    Hibbard, J. H., Mahoney, E. R., Stockard, J., & Tusler, M. (2004). Development of the Patient Activation Measure (PAM): Conceptualizing and measuring activation in patients and consumers. Health Services Research, 39, 1005–1026.CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Hibbard, J. H., Mahoney, E. R., Stockard, J., & Tusler, M. (2005). Development and testing of a short form of the Patient Activation Measure. HSR. Health Services Research, 40, 1918–1930.CrossRefPubMedGoogle Scholar
  18. 18.
    Hibbard, J. H., & Gilburt, H. (2014). Supporting people to manage their health: An introduction to patient activation. United Kingdom: The King’s Fund. Retrieved from http://www.kingsfund.org.uk/publications/supporting-people-manage-their-health.
  19. 19.
    Hinkle, D. E., Wiersma, W., & Jurs, S. G. (1998). Applied statistics for the behavioural sciences (4th ed.). Boston, MA: Houghton Mifflin Company.Google Scholar
  20. 20.
    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, 521–529.CrossRefPubMedGoogle Scholar
  21. 21.
    Insignia Health, L. L. C. (2011). Patient Activation Measure (PAM) 13 TM: license materials. Portland: Insignia Health.Google Scholar
  22. 22.
    Linacre, J. M. (1999). Investigating rating scale category utility. Journal of Outcome Measurement, 3(2), 103–122.PubMedGoogle Scholar
  23. 23.
    Linacre, J. M. (2002). Optimising rating scale category effectiveness. Journal of Applied Measurement, 3, 85–106.PubMedGoogle Scholar
  24. 24.
    Lorig, K. R., Sobel, D. S., Ritter, P. L., Laurent, D., & Hobbs, M. (2001). Effect of a self-management program for patients with chronic disease. Effective Clinical Practice, 4, 256–262.PubMedGoogle Scholar
  25. 25.
    Maindal, H. T., Sokolowski, I., & Vedsted, P. (2009). Translation, adaptation and validation of the American short form Patient Activation Measure (PAM-13) in a Danish version. BMC Public Health, 9, 209. doi:10.1186/1471-2458-9-209.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Magnezi, R., & Glasser, S. (2014). Psychometric properties of the Hebrew translation of the Patient Activation Measure (PAM-13). PLoS ONE, 9, e113391. doi:10.1371/journal.pone.0113391.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Magnezi, R., Glasser, S., Shalev, H., Sheiber, A., & Reuveni, H. (2014). Patient activation, depression and quality of life. Patient Education and Counselling, 94, 432–437.CrossRefGoogle Scholar
  28. 28.
    Mair, P., & Hatzinger, R. (2006). eRm; extended Rasch models. R package version 0.3.2. http://CRAN.R-project.org/. Accessed October, 2013.
  29. 29.
    Mair, P., & Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49, 26–43.Google Scholar
  30. 30.
    McDowell, I. (2006). Measuring health—A guide to rating scales and questionnaires. Oxford: Oxford University Press Inc.CrossRefGoogle Scholar
  31. 31.
    McHorney, C. A., & Tarlov, A. R. (1995). Individual-patient monitoring in clinical practice: are available health status surveys adequate? Quality of Life Research, 4, 293–307.CrossRefPubMedGoogle Scholar
  32. 32.
    Messick, S. (1995). Validity of psychological assessment: Validation of inferences from person’s responses and performances as scientific inquiry into score meaning. American Psychologist, 50, 741–749.CrossRefGoogle Scholar
  33. 33.
    Moljord, I. E. O., Lara-Cabrera, M. L., Perestelo-Perez, L., Rivero-Santana, A., Eriksen, L., & Linaker, O. M. (2015). Psychometric properties of the Patient Activation Measure-13 among out-patients waiting for mental health treatment: A validation study in Norway. Patient Education and Counselling, 98, 1410–1417. doi:10.1016/j.pec.2015.06.009.CrossRefGoogle Scholar
  34. 34.
    Ministry of Health, Singapore. (2011). National Health Survey. Retrieved from https://www.moh.gov.sg/content/dam/moh_web/Publications/Reports/2011/NHS2010%20-%20low%20res.pdf.
  35. 35.
    Ministry of Health, Singapore. (2014). Top 10 conditions of hospitalisation. Retrieved from https://www.moh.gov.sg/content/moh_web/home/statistics/Health_Facts_Singapore/Top_10_Conditions_of_Hospitalisation.html.
  36. 36.
    Ministry of Health, Singapore. (2014). Principal causes of death. Retrieved from https://www.moh.gov.sg/content/moh_web/home/statistics/Health_Facts_Singapore/Principal_Causes_of_Death.html.
  37. 37.
    Ministry of Health, Singapore. (2014). Disease burden. Retrieved from https://www.moh.gov.sg/content/moh_web/home/statistics/Health_Facts_Singapore/Disease_Burden.html.
  38. 38.
    Ngooi, B. X. (2016). Validation of the Patient Activation Measure (PAM-13) among adults with cardiac conditions in Singapore: A mixed methods study. Unpublished master’s thesis, Dalhousie University, Halifax, Canada.Google Scholar
  39. 39.
    Packer, T. L., Kephart, G., Ghahari, S., Audulv, A., Versnel, J., & Warner, G. (2015). The Patient Activation Measure: A validation study in a neurological population. Quality of Life Research,. doi:10.1007/s11136-014-0908-0.PubMedGoogle Scholar
  40. 40.
    R Development Core Team. (2006). R: A language and environment for statistical computing. Vienna: R Development Core Team.Google Scholar
  41. 41.
    Rademaker, J., Nijman, J., Heok, 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, 577–583.CrossRefGoogle Scholar
  42. 42.
    Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Danish Institute for Educational Research.Google Scholar
  43. 43.
    Reise, S. P., & Yu, J. (1990). Parameter recovery in the graded response model using MULTILOG. Journal of Educational Measurement, 27, 133–144.CrossRefGoogle Scholar
  44. 44.
    Renders, C. G., Valk, S., Griffin, E., Wagner, J. E. V., & Assendelft, W. (2001). Interventions to improve the management of diabetes in primary care, outpatient, and community settings. Diabetes Care, 24, 1821–1833.CrossRefPubMedGoogle Scholar
  45. 45.
    Saha, S., Koley, M., Mahoney, E. R., Hibbard, J., Ghosh, S., Goutam, N., et al. (2014). Patient Activation Measures in a government homeopathic hospital in India. Journal of Evidence-Based Complementary & Alternative Medicine,. doi:10.1177/2156587214540175.Google Scholar
  46. 46.
    Singapore Department of Statistics. (2010). Census of population 2010 statistical release 1: Demographics characteristics, education, language and religion. Retrieved from http://www.singstat.gov.sg/publications/publications_and_papers/cop2010/census10_stat_release1.html.
  47. 47.
    Singapore Department of Statistics. (2012). Key household income trends. Retrieved from http://www.singstat.gov.sg/publications/publications_and_papers/household_income_and_expenditure/pp-s19.pdf.
  48. 48.
    Sitzia, J. (1999). How valid and reliable are patient satisfaction data? An analysis of 195 studies. International Journal of Qualitative Health Care, 11, 319–328.CrossRefGoogle Scholar
  49. 49.
    Skolasky, R. L., Mackenzie, E. J., Wegener, S. T., & Riley, J. H. (2008). Patient activation and adherence to physical therapy in persons undergoing spine surgery. Spine, 33, E784–E791.CrossRefPubMedGoogle Scholar
  50. 50.
    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. HSR. Health Services Research, 46, 457–478.CrossRefPubMedGoogle Scholar
  51. 51.
    Skolasky, R. L., Mackenzie, E. J., Riley, L. H., & Stephen, T. W. (2009). Psychometric properties of the Patient Activation Measure among individuals presenting for elective lumbar spine surgery. Quality of Life Research, 18, 1357–1366.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Spitzer, R. L., Kroenke, K., Williams, J. B. W., & for the Patient Health Questionnaire Primary Care Study Group. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. JAMA, 272, 1749–1756.CrossRefGoogle Scholar
  53. 53.
    Stanford Patient Education Research Center. (2012). Self-efficacy for managing chronic disease 6-item scale. Retrieved from http://patienteducation.stanford.edu/research/secd6.html.
  54. 54.
    StataCorp. (2015). Stata 14 [computer software]. USA: StataCorp LP.Google Scholar
  55. 55.
    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, 1558–1567.CrossRefPubMedGoogle Scholar
  56. 56.
    Sung, S. C., Low, C. C., Fung, D. S., & Chan, Y. H. (2013). Screening for major and minor depression in a multiethnic sample of Asian primary care patients: A comparison of the nine-item Patient health questionnaire (PHQ-9) and the 16-item quick inventory of depressive symptomatology—self-report (QIDS-SR16). Asia-Pacific Psychiatry, 5, 249–258.CrossRefPubMedGoogle Scholar
  57. 57.
    Wagner, E. H., Austin, B. T., & Von Korff, M. (1996). Improving outcomes in chronic illness. Managed Care Quarterly, 4, 12–25.PubMedGoogle Scholar
  58. 58.
    World Health Organisation. (2013). Adherence to long-term therapies: Evidence for action. Retrieved from www.who.int/chp/knowledge/publications/adherence_full_report.pdf.
  59. 59.
    World Health Organisation. (2013). Health systems strengthening glossary. Retrieved from http://www.who.int/healthsystems/hss_glossary/en/index8.html.
  60. 60.
    Ueshima, H., Sekikawa, A., Miura, K., Turin, T. C., Takashima, N., Kita, Y., et al. (2008). Cardiovascular disease and risk factors in Asia: A selected review. Circulation, 118, 2702–2709.CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    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 (PAM 13). BMC Public Health, 13, 1027. doi:10.1186/1471-2458-13-1027.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of RehabilitationNational University HospitalSingaporeSingapore
  2. 2.School of Occupational TherapyDalhousie UniversityHalifaxCanada
  3. 3.Department of Community Health and EpidemiologyDalhousie UniversityHalifaxCanada
  4. 4.Department of NursingNational University HospitalSingaporeSingapore
  5. 5.Department of CardiologyNational University Heart CentreSingaporeSingapore

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