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The purpose of this study was to test the internal consistency and construct validity of the revised 12-item self-rated Partners in Health (PIH) scale used to assess patients’ chronic condition self-management knowledge and behaviours.
Baseline PIH data were collected for a total of 294 patients with a range of co-morbid chronic conditions including diabetes, cardiovascular disease and arthritis. Scale data for the initial sample of 176 patients were analysed for internal consistency and construct validity using Reliability Analysis and Factor Analysis. Construct validity was tested in a separate sample of 118 patients using confirmatory factor analysis and a structural equation model.
Good internal consistency was indicated with a Cronbach’s alpha coefficient of 0.82 in the initial sample. Factor analysis for this sample revealed four key factors (knowledge, coping, management of condition and adherence to treatment) across the twelve items of the scale. These four key factors were then confirmed by applying the exploratory structural equation model to the separate sample.
The PIH scale exhibits construct validity and internal consistency. It therefore is both a generic self-rated clinical tool for assessing self-management in a range of chronic conditions as well as an outcome measure to compare populations and change in patient self-management knowledge and behaviour over time. The four domains of self-management provide a valid measure of patient competency in relation to the self-management of their chronic condition(s).
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Centre for Health Advancement, KPMG Management Consulting. (1999). The Australian Coordinated Care Trials: Interim Technical National Evaluation Report. Canberra: Commonwealth Department of Health and Family Services.
Battersby, M. W., Ask, A., Reece, M., Markwick, M., & Collins, J. (2003). The partners in health scale: The development and psychometric properties of a generic assessment scale for chronic condition self-management. Australian Journal of Primary Health, 9(2&3), 41–52. CrossRef
Battersby, M. W., FHBHRU training team. The ‘Flinders Program’ of Chronic Condition Self- Management: Information Paper. Adelaide: Flinders University, Adelaide Available from: http://som.flinders.edu.au/FUSA/CCTU/self_management.htm#sixPrinciples.
Battersby, M. W., Allen, K., Conroy, P., Fox, J., McAlindon, A., & Kalucy, L., et al. (1998). Implementing a health outcomes approach in coordinated care. The health outcomes conference: implementing the health outcomes approach. Canberra.
Francis, C., Feyer, A., & Smith, B. J. (2007). Implementing chronic disease self-management in community settings: Lessons from Australian demonstration projects. Australian Health Review, 31(4), 449–509. CrossRef
Harvey, P. W. (2001). The impact of coordinated care: Eyre Region, South Australia. Australian Journal of Rural Health (AJRH), 9(2), 70–74. CrossRef
Mills, P. D., & Harvey, P. W. (2003). Beyond community-based diabetes management and the COAG Coordinated Care Trial. Australian Journal of Rural Health 11(3).
Commonwealth of Australia. (2001). The Australian coordinated care trials: Final Technical National Evaluation Report on the First Round of Trials, July 2001. Canberra: Commonwealth Department of Health and Aged Care.
Battersby, M. W. (2005). Health reform through coordinated care: SA HealthPlus. BMJ 330(March 19):662–665.
Ah Kit, J., Prideaux, C., Harvey, P. W., Collins, J. P., Battersby, M. W., & Mills, P. D. (2003). Chronic disease self-management in Aboriginal communities: Towards a sustainable program of care in rural communities. Australian Journal of Primary Health, 9(23), 168–176. CrossRef
Hambleton, R. K., & Jones, R. W. (1993). Comparison of classical test theory and item response theory and their application to test development. Educational measurement, 12(3), 38–47.
Stage, C. (2003). Classical test theory or item response theory; the Swedish experience. Educational measurement 42.
Norman, G. R., & Streiner, D. L. (1994). Biostatistics: the bare essentials. St Louis.
Hair, J. E., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Upper Saddle River, USA: Prentice Hall.
Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276. CrossRef
Ledesma, D., & Valero-Mora, P. (2007). Determining the number of factors to retain in EFA: an easy-to-use computer program for carrying out parallel analysis. Practical Assessment, Research and Evaluation 12(2).
Rubinstein, R. Y. (1981). Simulation and the monte carlo method. New York: Wiley. CrossRef
Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In G. D. Goffin & E. Helmes (Eds.), Problems and solutions in human assessment. Boston, pp 44–71.
Lance, C. E., Butts, M. M., & Michaels, L. C. (2006). The sources of four commonly reported cutoff criteria: What did they really say? Organizational Research Methods, 9(2), 202–220. CrossRef
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. CrossRef
- The internal consistency and construct validity of the partners in health scale: validation of a patient rated chronic condition self-management measure
- Springer Netherlands